Data scientist jobs in Englewood, NJ

NYC NY / Hybrid 12+ Months Project - Leveraging Llama to extract cybersecurity insights out of unstructured data from their ticketing system. Must have strong experience with: Llama Python Hadoop MCP Machine Learning (ML) They need a strong developer - using llama and Hadoop (this is where the data sits), experience with MCP. They have various ways to pull the data out of their tickets but want someone who can come in and make recommendations on the best way to do it and then get it done. They have tight timelines. Thanks and Regards! Lavkesh Dwivedi ************************ Amtex System Inc. 28 Liberty Street, 6th Floor | New York, NY - 10005 ************ ********************

Data Engineer - Data Migration Project 6-Month Contract (ASAP Start) Hybrid - Manhattan, NY (3 days/week) We are seeking a Data Engineer to support a critical data migration initiative for a leading sports entertainment and gaming company headquartered in Manhattan, NY. This role will focus on transitioning existing data workflows and analytics pipelines from Amazon Redshift to Databricks, optimizing performance and ensuring seamless integration across operational reporting systems. The ideal candidate will have strong SQL and Python skills, experience working with Salesforce data, and a background in data engineering, ETL, or analytics pipeline optimization. This is a hybrid role requiring collaboration with cross-functional analytics, engineering, and operations teams to enhance data reliability and scalability. Minimum Qualifications: Advanced proficiency in SQL, Python, and SOQL Hands-on experience with Databricks, Redshift, Salesforce, and DataGrip Experience building and optimizing ETL workflows and pipelines Familiarity with Tableau for analytics and visualization Strong understanding of data migration and transformation best practices Ability to identify and resolve discrepancies between data environments Excellent analytical, troubleshooting, and communication skills Responsibilities: Modify and migrate existing workflows and pipelines from Redshift to Databricks. Rebuild data preprocessing structures that prepare Salesforce data for Tableau dashboards and ad hoc analytics. Identify and map Redshift data sources to their Databricks equivalents, accounting for any structural or data differences. Optimize and consolidate 200+ artifacts to improve efficiency and reduce redundancy. Implement Databricks-specific improvements to leverage platform capabilities and enhance workflow performance. Collaborate with analytics and engineering teams to ensure data alignment across business reporting systems. Apply a “build from scratch” mindset to design scalable, modernized workflows rather than direct lift-and-shift migrations. Identify dependencies on data sources not yet migrated and assist in prioritization efforts with the engineering team. What's in it for you? Opportunity to lead a high-impact data migration initiative at a top-tier gaming and entertainment organization. Exposure to modern data platforms and architecture, including Databricks and advanced analytics workflows. Collaborative environment with visibility across analytics, operations, and engineering functions. Ability to contribute to the foundation of scalable, efficient, and data-driven decision-making processes. EEO Statement: Eight Eleven Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.

DL Software produces Godel, a financial information and trading terminal. Role Description This is a full-time, on-site role based in New York, NY, for a Data Engineer. The Data Engineer will design, build, and maintain scalable data systems and pipelines. Responsibilities include data modeling, developing and managing ETL workflows, optimizing data storage solutions, and supporting data warehousing initiatives. The role also involves collaborating with cross-functional teams to improve data accessibility and analytics capabilities. Qualifications Strong proficiency in Data Engineering and Data Modeling Mandatory: strong experience in global financial instruments including equities, fixed income, options and exotic asset classes Strong Python background Expertise in Extract, Transform, Load (ETL) processes and tools Experience in designing, managing, and optimizing Data Warehousing solutions

Godel Terminal is a cutting edge financial platform that puts the world's financial data at your fingertips. From Equities and SEC filings, to global news delivered in milliseconds, thousands of customers rely on Godel every day to be their guide to the world of finance. We are looking for a senior engineer in New York City to join our team and help build out live data services as well as historical data for US markets and international exchanges. This position will specifically work on new asset classes and exchanges, but will be expected to contribute to the core architecture as we expand to international markets. Our team works quickly and efficiently, we are opinionated but flexible when it's time to ship. We know what needs to be done, and how to do it. We are laser focused on not just giving our customers what they want, but exceeding their expectations. We are very proud that when someone opens the app the first time they ask: “How on earth does this work so fast”. If that sounds like a team you want to be part of, here is what we need from you: Minimum qualifications: Able to work out of our Manhattan office minimum 4 days a week 5+ years of experience in a financial or startup environment 5+ years of experience working on live data as well as historical data 3+ years of experience in Java, Python, and SQL Experience managing multiple production ETL pipelines that reliably store and validate financial data Experience launching, scaling, and improving backend services in cloud environments Experience migrating critical data across different databases Experience owning and improving critical data infrastructure Experience teaching best practices to junior developers Preferred qualifications: 5+ years of experience in a fintech startup 5+ years of experience in Java, Kafka, Python, PostgreSQL 5+ years of experience working with Websockets like RXStomp or Socket.io 5+ years of experience wrangling cloud providers like AWS, Azure, GCP, or Linode 2+ years of experience shipping and optimizing Rust applications Demonstrated experience keeping critical systems online Demonstrated creativity and resourcefulness under pressure Experience with corporate debt / bonds and commodities data Salary range begins at $150,000 and increases with experience Benefits: Health Insurance, Vision, Dental To try the product, go to *************************

· Expert level skills writing and optimizing complex SQL · Experience with complex data modelling, ETL design, and using large databases in a business environment · Experience with building data pipelines and applications to stream and process datasets at low latencies · Fluent with Big Data technologies like Spark, Kafka and Hive · Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service is required · Designing and building of data pipelines using API ingestion and Streaming ingestion methods · Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential · Experience in developing NO SQL solutions using Azure Cosmos DB is essential · Thorough understanding of Azure and AWS Cloud Infrastructure offerings · Working knowledge of Python is desirable · Designing and implementing scalable and secure data processing pipelines using Azure Data Factory, Azure Databricks, and other Azure services · Managing and optimizing data storage using Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Cosmos DB · Monitoring and troubleshooting data-related issues within the Azure environment to maintain high availability and performance · Implementing data security measures, including encryption, access controls, and auditing, to protect sensitive information · Automating data pipelines and workflows to streamline data ingestion, processing, and distribution tasks · Utilizing Azure's analytics services, such as Azure Synapse Analytics, to provide insights and support data-driven decision-making. · Documenting data procedures, systems, and architectures to maintain clarity and ensure compliance with regulatory standards · Providing guidance and support for data governance, including metadata management, data lineage, and data cataloging Best Regards, Dipendra Gupta Technical Recruiter *****************************

Are you a data engineer who loves building systems that power real impact in the world? A fast growing healthcare technology organization is expanding its innovation team and is looking for a Data Engineer II to help build the next generation of its data platform. This team sits at the center of a major transformation effort, partnering closely with engineering, analytics, and product to design the foundation that supports advanced automation, AI, intelligent workflows, and high scale data operations that drive measurable outcomes for hospitals, health systems, and medical groups. In this role, you will design, develop, and maintain software applications that process large volumes of data every day. You will collaborate with cross functional teams to understand data requirements, build and optimize data models, and create systems that ensure accuracy, reliability, and performance. You will write code that extracts, transforms, and loads data from a variety of sources into modern data warehouses and data lakes, while implementing best in class data quality and governance practices. You will work hands on with big data technologies such as Hadoop, Spark, and Kafka, and you will play a critical role in troubleshooting, performance tuning, and ensuring the scalability of complex data applications. To thrive here, you should bring strong problem solving ability, analytical thinking, and excellent communication skills. This is an opportunity to join an expanding innovation group within a leading healthcare platform that is investing heavily in data, AI, and the future of intelligent revenue operations. If you want to build systems that make a real difference and work with teams that care deeply about improving patient experiences and provider performance, this is a chance to do highly meaningful engineering at scale.

Title: Enterprise Data Management - Data Cloud, Senior Developer I Duration: FTE/Permanent Salary: 130-165k The Data Engineering team oversees the organization's central data infrastructure, which powers enterprise-wide data products and advanced analytics capabilities in the investment management sector. We are seeking a senior cloud data engineer to spearhead the architecture, development, and rollout of scalable, reusable data pipelines and products, emphasizing the creation of semantic data layers to support business users and AI-enhanced analytics. The ideal candidate will work hand-in-hand with business and technical groups to convert intricate data needs into efficient, cloud-native solutions using cutting-edge data engineering techniques and automation tools. Responsibilities: Collaborate with business and technical stakeholders to collect requirements, pinpoint data challenges, and develop reliable data pipeline and product architectures. Design, build, and manage scalable data pipelines and semantic layers using platforms like Snowflake, dbt, and similar cloud tools, prioritizing modularity for broad analytics and AI applications. Create semantic layers that facilitate self-service analytics, sophisticated reporting, and integration with AI-based data analysis tools. Build and refine ETL/ELT processes with contemporary data technologies (e.g., dbt, Python, Snowflake) to achieve top-tier reliability, scalability, and efficiency. Incorporate and automate AI analytics features atop semantic layers and data products to enable novel insights and process automation. Refine data models (including relational, dimensional, and semantic types) to bolster complex analytics and AI applications. Advance the data platform's architecture, incorporating data mesh concepts and automated centralized data access. Champion data engineering standards, best practices, and governance across the enterprise. Establish CI/CD workflows and protocols for data assets to enable seamless deployment, monitoring, and versioning. Partner across Data Governance, Platform Engineering, and AI groups to produce transformative data solutions. Qualifications: Bachelor's or Master's in Computer Science, Information Systems, Engineering, or equivalent. 10+ years in data engineering, cloud platform development, or analytics engineering. Extensive hands-on work designing and tuning data pipelines, semantic layers, and cloud-native data solutions, ideally with tools like Snowflake, dbt, or comparable technologies. Expert-level SQL and Python skills, plus deep familiarity with data tools such as Spark, Airflow, and cloud services (e.g., Snowflake, major hyperscalers). Preferred: Experience containerizing data workloads with Docker and Kubernetes. Track record architecting semantic layers, ETL/ELT flows, and cloud integrations for AI/analytics scenarios. Knowledge of semantic modeling, data structures (relational/dimensional/semantic), and enabling AI via data products. Bonus: Background in data mesh designs and automated data access systems. Skilled in dev tools like Azure DevOps equivalents, Git-based version control, and orchestration platforms like Airflow. Strong organizational skills, precision, and adaptability in fast-paced settings with tight deadlines. Proven self-starter who thrives independently and collaboratively, with a commitment to ongoing tech upskilling. Bonus: Exposure to BI tools (e.g., Tableau, Power BI), though not central to the role. Familiarity with investment operations systems (e.g., order management or portfolio accounting platforms).

Title: Senior Azure Data Engineer Client: Major Japanese Bank Experience Level: Senior (10+ Years) The Senior Azure Data Engineer will design, build, and optimize enterprise data solutions within Microsoft Azure for a major Japanese bank. This role focuses on architecting scalable data pipelines, enhancing data lake environments, and ensuring security, compliance, and data governance best practices. Key Responsibilities: Develop, maintain, and optimize Azure-based data pipelines and ETL/ELT workflows. Design and implement Azure Data Lake, Synapse, Databricks, and ADF solutions. Ensure data security, compliance, lineage, and governance controls. Partner with architecture, data governance, and business teams to deliver high-quality data solutions. Troubleshoot performance issues and improve system efficiency. Required Skills: 10+ years of data engineering experience. Strong hands-on expertise with Azure Synapse, Azure Data Factory, Azure Databricks, Azure Data Lake, and Azure SQL. Azure certifications strongly preferred. Strong SQL, Python, and cloud data architecture skills. Experience in financial services or large enterprise environments preferred.

Senior Data Engineer (Snowflake & Python) 1-Year Contract | $60/hour + Benefit Options Hybrid: On-site a few days per month (local candidates only) Work Authorization Requirement You must be authorized to work for any employer as a W2 employee. This is required for this role. This position is W-2 only - no C2C, no third-party submissions, and no sponsorship will be considered. Overview We are seeking a Senior Data Engineer to support enterprise-scale data initiatives for a highly collaborative engineering organization. This is a new, long-term contract opportunity for a hands-on data professional who thrives in fast-paced environments and enjoys building high-quality, scalable data solutions on Snowflake. Candidates must be based in or around New Jersey, able to work on-site at least 3 days per month, and meet the W2 employment requirement. What You'll Do Design, develop, and support enterprise-level data solutions with a strong focus on Snowflake Participate across the full software development lifecycle - planning, requirements, development, testing, and QA Partner closely with engineering and data teams to identify and implement optimal technical solutions Build and maintain high-performance, scalable data pipelines and data warehouse architectures Ensure platform performance, reliability, and uptime, maintaining strong coding and design standards Troubleshoot production issues, identify root causes, implement fixes, and document preventive solutions Manage deliverables and priorities effectively in a fast-moving environment Contribute to data governance practices including metadata management and data lineage Support analytics and reporting use cases leveraging advanced SQL and analytical functions Required Skills & Experience 8+ years of experience designing and developing data solutions in an enterprise environment 5+ years of hands-on Snowflake experience Strong hands-on development skills with SQL and Python Proven experience designing and developing data warehouses in Snowflake Ability to diagnose, optimize, and tune SQL queries Experience with Azure data frameworks (e.g., Azure Data Factory) Strong experience with orchestration tools such as Airflow, Informatica, Automic, or similar Solid understanding of metadata management and data lineage Hands-on experience with SQL analytical functions Working knowledge of Shell scripting and Java scripting Experience using Git, Confluence, and Jira Strong problem-solving and troubleshooting skills Collaborative mindset with excellent communication skills Nice to Have Experience supporting Pharma industry data Exposure to Omni-channel data environments Why This Opportunity $60/hour W2 on a long-term 1-year contract Benefit options available Hybrid structure with limited on-site requirement High-impact role supporting enterprise data initiatives Clear expectations: W-2 only, no third-party submissions, no Corp-to-Corp This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron's progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,500+, and has 58 offices in 21 countries within key global markets. Our challenge We are seeking an experienced Lead Data Engineer to spearhead our data infrastructure initiatives. The ideal candidate will have a strong background in building scalable data pipelines, with hands-on expertise in Kafka, Snowflake, and Python. As a key technical leader, you will design and maintain robust streaming and batch data architectures, optimize data loads in Snowflake, and drive automation and best practices across our data platform. Additional Information* The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within New York, NY is $135k - $140k/year & benefits (see below). The Role Responsibilities: Design, develop, and maintain reliable, scalable data pipelines leveraging Kafka, Snowflake, and Python. Lead the implementation of distributed data processing and real-time streaming solutions. Manage Snowflake data warehouse environments, including data loading, tuning, and optimization for performance and cost-efficiency. Develop and automate data workflows and transformations using Python scripting. Collaborate with data scientists, analysts, and stakeholders to translate business requirements into technical solutions. Monitor, troubleshoot, and optimize data pipelines and platform performance. Ensure data quality, governance, and security standards are upheld. Guide and mentor junior team members and foster best practices in data engineering. Requirements: Proven experience in building and maintaining data pipelines, especially using Kafka, Snowflake, and Python. Strong expertise in distributed data processing frameworks and streaming architectures. Hands-on experience with Snowflake data warehouse platform, including data ingestion, performance tuning, and management. Proficiency in Python for data manipulation, automation, and scripting. Familiarity with Kafka ecosystem tools such as Confluent, Kafka Connect, and Kafka Streams. Solid understanding of SQL, data modeling, and ETL/ELT processes. Knowledge of cloud platforms (AWS, Azure, GCP) is advantageous. Strong troubleshooting skills and ability to optimize data workflows. Excellent communication and collaboration skills. Preferred, but not required: Bachelor's or Master's degree in Computer Science, Information Systems, or related field. Experience with containerization (Docker, Kubernetes) is a plus. Knowledge of data security best practices and GDPR compliance. Certifications related to cloud platforms or data engineering preferred. We offer: A highly competitive compensation and benefits package. A multinational organization with 58 offices in 21 countries and the possibility to work abroad. 10 days of paid annual leave (plus sick leave and national holidays). Maternity & paternity leave plans. A comprehensive insurance plan including medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region). Retirement savings plans. A higher education certification policy. Commuter benefits (varies by region). Extensive training opportunities, focused on skills, substantive knowledge, and personal development. On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses. Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups. Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms. A flat and approachable organization. A truly diverse, fun-loving, and global work culture. SYNECHRON'S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference' is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Haptiq is a leader in AI-powered enterprise operations, delivering digital solutions and consulting services that drive value and transform businesses. We specialize in using advanced technology to streamline operations, improve efficiency, and unlock new revenue opportunities, particularly within the private capital markets. Our integrated ecosystem includes PaaS - Platform as a Service, the Core Platform, an AI-native enterprise operations foundation built to optimize workflows, surface insights, and accelerate value creation across portfolios; SaaS - Software as a Service, a cloud platform delivering unmatched performance, intelligence, and execution at scale; and S&C - Solutions and Consulting Suite, modular technology playbooks designed to manage, grow, and optimize company performance. With over a decade of experience supporting high-growth companies and private equity-backed platforms, Haptiq brings deep domain expertise and a proven ability to turn technology into a strategic advantage. The Opportunity As a Data Engineer within the Global Operations team, you will be responsible for managing the internal data infrastructure, building and maintaining data pipelines, and ensuring the integrity, cleanliness, and usability of data across our critical business systems. This role will play a foundational part in developing a scalable internal data capability to drive decision-making across Haptiq's operations. Responsibilities and Duties Design, build, and maintain scalable ETL/ELT pipelines to consolidate data from delivery, finance, and HR systems (e.g., Kantata, Salesforce, JIRA, HRIS platforms). Ensure consistent data hygiene, normalization, and enrichment across source systems. Develop and maintain data models and data warehouses optimized for analytics and operational reporting. Partner with business stakeholders to understand reporting needs and ensure the data structure supports actionable insights. Own the documentation of data schemas, definitions, lineage, and data quality controls. Collaborate with the Analytics, Finance, and Ops teams to build centralized reporting datasets. Monitor pipeline performance and proactively resolve data discrepancies or failures. Contribute to architectural decisions related to internal data infrastructure and tools. Requirements 3-5 years of experience as a data engineer, analytics engineer, or similar role. Strong experience with SQL, data modeling, and pipeline orchestration (e.g., Airflow, dbt). Hands-on experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift). Experience working with REST APIs and integrating with SaaS platforms like Salesforce, JIRA, or Workday. Proficiency in Python or another scripting language for data manipulation. Familiarity with modern data stack tools (e.g., Fivetran, Stitch, Segment). Strong understanding of data governance, documentation, and schema management. Excellent communication skills and ability to work cross-functionally. Benefits Flexible work arrangements (including hybrid mode) Great Paid Time Off (PTO) policy Comprehensive benefits package (Medical / Dental / Vision / Disability / Life) Healthcare and Dependent Care Flexible Spending Accounts (FSAs) 401(k) retirement plan Access to HSA-compatible plans Pre-tax commuter benefits Employee Assistance Program (EAP) Opportunities for professional growth and development. A supportive, dynamic, and inclusive work environment. Why Join Us? We value creative problem solvers who learn fast, work well in an open and diverse environment, and enjoy pushing the bar for success ever higher. We do work hard, but we also choose to have fun while doing it. The compensation range for this role is $75,000 to $80,000 USD

Our client is a growing Fintech software company Headquarted in New York, NY. They have several hundred employees and are in growth mode. They are currently looking for a Senior Data Engineer w/ 6+ years of overall professional experience. Qualified candidates will have hands-on experience with Python (6 years), SQL (6 years), DBT (3 years), AWS (Lambda, Glue), Airflow and Snowflake (3 years). BSCS and good CS fundamentals. The Senior Data Engineer will work in a collaborative team environment and will be responsible for building, optimizing and scaling ETL Data Pipelines, DBT models and Datawarehousing. Excellent communication and organizational skills are expected. This role features competitive base salary, equity, 401(k) with company match and many other attractive perks. Please send your resume to ******************* for immediate consideration.

LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 750 clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree - a Larsen & Toubro Group company - combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. For more information, please visit ******************* Job Title: Principal Data Modeler / Data Architecture Lead - Capital Markets Work Location Jersey City, NJ (Onsite, 5 days / week) Job Description: We are seeking a highly experienced Principal Data Modeler / Data Architecture Lead to reverse engineer an existing logical data model supporting all major lines of business in the capital markets domain. The ideal candidate will have deep capital markets domain expertise and will work closely with business and technology stakeholders to elicit and document requirements, map those requirements to the data model, and drive enhancements or rationalization of the logical model prior to its conversion to a physical data model. A software development background is not required. Key Responsibilities Reverse engineers the current logical data model, analyzing entities, relationships, and subject areas across capital markets (including customer, account, portfolio, instruments, trades, settlement, funds, reporting, and analytics). Engage with stakeholders (business, operations, risk, finance, compliance, technology) to capture and document business and functional requirements, and map these to the data model. Enhance or streamline the logical data model, ensuring it is fit-for-purpose, scalable, and aligned with business needs before conversion to a physical model. Lead the logical-to-physical data model transformation, including schema design, indexing, and optimization for performance and data quality. Perform advanced data analysis using SQL or other data analysis tools to validate model assumptions, support business decisions, and ensure data integrity. Document all aspects of the data model, including entity and attribute definitions, ERDs, source-to-target mappings, and data lineage. Mentor and guide junior data modelers, providing coaching, peer reviews, and best practices for modeling and documentation. Champion a detail-oriented and documentation-first culture within the data modeling team. Qualifications Minimum 15 years of experience in data modeling, data architecture, or related roles within capital markets or financial services. Strong domain expertise in capital markets (e.g., trading, settlement, reference data, funds, private investments, reporting, analytics). Proven expertise in reverse engineering complex logical data models and translating business requirements into robust data architectures. Strong skills in data analysis using SQL and/or other data analysis tools. Demonstrated ability to engage with stakeholders, elicit requirements, and produce high-quality documentation. Experience in enhancing, rationalizing, and optimizing logical data models prior to physical implementation. Ability to mentor and lead junior team members in data modeling best practices. Passion for detail, documentation, and continuous improvement. Software development background is not required. Preferred Skills Experience with data modeling tools (e.g., ER/Studio, ERwin, Power Designer). Familiarity with capital markets, business processes and data flows. Knowledge of regulatory and compliance requirements in financial data management. Exposure to modern data platforms (e.g., Snowflake, Databricks, cloud databases). Benefits and Perks: Comprehensive Medical Plan Covering Medical, Dental, Vision Short Term and Long-Term Disability Coverage 401(k) Plan with Company match Life Insurance Vacation Time, Sick Leave, Paid Holidays Paid Paternity and Maternity Leave LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, colour, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.

Distinguished Data Engineers are individual contributors who strive to be diverse in thought so we visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions. Horzianal, Bank data organization to accelerate data modernization across the bank by defining, building, and operating on a unified, resilient, and compliant Enterprise Data Platforms. Enable bank domains to produce and leverage modern data for a modern bank. The position focused on setting the technical vision, prototyping and driving the most complex data domain data architecture for the banking domains. In addition, partner closely with enterprise teams to develop highly resilient data platforms. Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices Visionaries, collaborating on Capital One's toughest issues, to deliver on business needs that directly impact the lives of our customers and associates Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled capabilities Responsibilities: Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in Strike the right balance between lending expertise and providing an inclusive environment where others' ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One's Tech talent Basic Qualifications: Bachelor's Degree At least 7 years of experience in data engineering At least 3 years of experience in data architecture At least 2 years of experience building applications in AWS Preferred Qualifications: Masters' Degree 9+ years of experience in data engineering 3+ years of data modeling experience 2+ years of experience with ontology standards for defining a domain 2+ years of experience using Python, SQL or Scala 1+ year of experience deploying machine learning models 3+ years of experience implementing big data processing solutions on AWS Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $263,900 - $301,200 for Distinguished Data Engineer Philadelphia, PA: $239,900 - $273,800 for Distinguished Data Engineer Richmond, VA: $239,900 - $273,800 for Distinguished Data Engineer Wilmington, DE: $239,900 - $273,800 for Distinguished Data Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Your work will change lives. Including your own. Please note: Our offices will be closed for our annual winter break from December 22, 2025, to January 2, 2026. Our response to your application will be delayed. The Impact You'll Make As a member of Recursion's AI-driven drug discovery initiatives, you will be at the forefront of reimagining how biological knowledge is generated, stored, accessed, and reasoned upon by LLMs. You will play a key role in developing the biological reasoning infrastructure, connecting large-scale data and codebases with dynamic, agent-driven AI systems.You will be responsible for defining the architecture that grounds our agents in biological truth. This involves integrating biomedical resources to enable AI systems to reason effectively and selecting the most appropriate data retrieval strategies to support those insights. This is a highly collaborative role: you will partner with machine learning engineers, biologists, chemists, and platform teams to build the connective tissue that allows our AI agents to reason like a scientist. The ideal candidate possesses deep expertise in both core bioinformatics/cheminformatics libraries and modern GenAI frameworks (including RAG and MCP), a strong architectural vision, and the ability to translate high-potential prototypes into scalable production workflows. In this role, you will: * Architect and maintain robust infrastructure to keep critical internal and external biological resources (e.g., ChEMBL, Ensembl, Reactome, proprietary assays) up-to-date and accessible to reasoning agents. * Design sophisticated context retrieval strategies, choosing the most effective approach for each biological use case, whether working with structured, entity-focused data, unstructured RAG, or graph-based representations. * Integrate established bioinformatics/cheminformatics libraries into a GenAI ecosystem, creating interfaces (such as via MCP) that allow agents to autonomously query and manipulate biological data. * Pilot methods for tool use by LLMs, enabling the system to perform complex tasks like pathway analysis on the fly rather than relying solely on memorized weights. * Develop scalable, production-grade systems that serve as the backbone for Recursion's automated scientific reasoning capabilities. * Collaborate cross-functionally with Recursion's core biology, chemistry, data science and engineering teams to ensure our biological data and the reasoning engines are accurately reflecting the complexity of disease biology and drug discovery. * Present technical trade-offs (e.g., graph vs. vector) to leadership and stakeholders in a clear, compelling way that aligns technical reality with product vision. The Team You'll Join You'll join a bold, agile team of scientists and engineers dedicated to building comprehensive biological maps by integrating Recursion's in-house datasets, patient data, and external knowledge layers to enable sophisticated agent-based reasoning. Within this cross-functional team, you will design and maintain the biological context and data structures that allow agents to reason accurately and efficiently. You'll collaborate closely with wet-lab biologists and core platform engineers to develop systems that are not only technically robust but also scientifically rigorous. The ideal candidate is curious about emerging AI technologies, passionate about making biological data both machine-readable and machine-understandable, and brings a strong foundation in systems biology, biomedical data analysis, and agentic AI systems. The Experience You'll Need * PhD in a relevant field (Bioinformatics, Cheminformatics, Computational Biology, Computer Science, Systems Biology) with 5+ years of industry experience, or MS in a relevant field with 7+ years of experience, focusing on biological data representation and retrieval. * Proficiency in utilizing major public biological databases (NCBI, Ensembl, STRING, GO) and using standard bioinformatics/cheminformatics toolkits (e.g., RDKit, samtools, Biopython). * Strong skills in designing and maintaining automated data pipelines that support continuous ingestion, transformation, and refresh of biological data without manual intervention. * Ability to work with knowledge graph data models and query languages (e.g., RDF, SPARQL, OWL) and translate graph-structured data into relational or other non-graph representations, with a strong judgment in evaluating trade-offs between different approaches. * Competence in building and operating GenAI stacks, including RAG systems, vector databases, and optimization of context windows for large-scale LLM deployments. * Hands-on expertise with agentic AI frameworks (e.g., MCP, Google ADK, LangChain, AutoGPT) and familiarity with leading LLMs (e.g., Google Gemini/Gemma) in agentic workflows, including benchmarking and evaluating agent performance on bioinformatics/cheminformatics tasks such as structure prediction, target identification, and pathway mapping. * Strong Python skills and adherence to software engineering best practices, including CI/CD, Git-based version control, and modular design. * Excellent cross-functional communication skills, ability to clearly explain complex architectural decisions to both scientific domain experts and technical stakeholders. Nice to Have * Strong background in machine learning and deep learning, including hands-on experience with foundation models and modern neural architectures. * Fine-tuning LLMs on scientific corpora for domain-specific reasoning. * Integrating LLMs with experimental or proprietary assay data in live scientific workflows. * Background in drug discovery and target identification. * Meaningful contributions to open-source libraries, research codebases, or community-driven tools. Working Location & Compensation: This is an office-based, hybrid role in either our Salt Lake City, UT or New York City, NY offices. Employees are expected to work in the office at least 50% of the time. At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $200,600 - $238,400. You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. #LI-DNI The Values We Hope You Share: * We act boldly with integrity. We are unconstrained in our thinking, take calculated risks, and push boundaries, but never at the expense of ethics, science, or trust. * We care deeply and engage directly. Caring means holding a deep sense of responsibility and respect - showing up, speaking honestly, and taking action. * We learn actively and adapt rapidly. Progress comes from doing. We experiment, test, and refine, embracing iteration over perfection. * We move with urgency because patients are waiting. Speed isn't about rushing but about moving the needle every day. * We take ownership and accountability. Through ownership and accountability, we enable trust and autonomy-leaders take accountability for decisive action, and teams own outcomes together. * We are One Recursion. True cross-functional collaboration is about trust, clarity, humility, and impact. Through sharing, we can be greater than the sum of our individual capabilities. Our values underpin the employee experience at Recursion. They are the character and personality of the company demonstrated through how we communicate, support one another, spend our time, make decisions, and celebrate collectively. More About Recursion Recursion (NASDAQ: RXRX) is a clinical stage TechBio company leading the space by decoding biology to radically improve lives. Enabling its mission is the Recursion OS, a platform built across diverse technologies that continuously generate one of the world's largest proprietary biological and chemical datasets. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale - up to millions of wet lab experiments weekly - and massive computational scale - owning and operating one of the most powerful supercomputers in the world, Recursion is uniting technology, biology and chemistry to advance the future of medicine. Recursion is headquartered in Salt Lake City, where it is a founding member of BioHive, the Utah life sciences industry collective. Recursion also has offices in Toronto, Montréal, New York, London, Oxford area, and the San Francisco Bay area. Learn more at ****************** or connect on X (formerly Twitter) and LinkedIn. Recursion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, local, or provincial human rights legislation. Accommodations are available on request for candidates taking part in all aspects of the selection process. Recruitment & Staffing Agencies: Recursion Pharmaceuticals and its affiliate companies do not accept resumes from any source other than candidates. The submission of resumes by recruitment or staffing agencies to Recursion or its employees is strictly prohibited unless contacted directly by Recursion's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Recursion, and Recursion will not owe any referral or other fees. Our team will communicate directly with candidates who are not represented by an agent or intermediary unless otherwise agreed to prior to interviewing for the job.

About Gap Inc. Our brands bridge the gaps we see in the world. Old Navy democratizes style to ensure everyone has access to quality fashion at every price point. Athleta unleashes the potential of every woman, regardless of body size, age or ethnicity. Banana Republic believes in sustainable luxury for all. And Gap inspires the world to bring individuality to modern, responsibly made essentials. This simple idea-that we all deserve to belong, and on our own terms-is core to who we are as a company and how we make decisions. Our team is made up of thousands of people across the globe who take risks, think big, and do good for our customers, communities, and the planet. Ready to learn fast, create with audacity and lead boldly? Join our team. About the Role Gap Inc. is seeking a Principal Data Scientist with deep expertise in operations research and machine learning to lead the design and deployment of advanced analytics solutions across the Product-to-Market (P2M) space. This role focuses on driving enterprise-scale impact through optimization and data science initiatives spanning pricing, inventory, and assortment optimization. The Principal Data Scientist serves as a senior technical and strategic thought partner, defining solution architectures, influencing product and business decisions, and ensuring that analytical solutions are both technically rigorous and operationally viable. The ideal candidate can lead end-to-end solutioning independently, manage ambiguity and complex stakeholder dynamics, and communicate technical and business risk effectively across teams and leadership levels. What You'll Do * Lead the framing, design, and delivery of advanced optimization and machine learning solutions for high-impact retail supply chain challenges. * Partner with product, engineering, and business leaders to define analytics roadmaps, influence strategic priorities, and align technical investments with business goals. * Provide technical leadership to other data scientists through mentorship, design reviews, and shared best practices in solution design and production deployment. * Evaluate and communicate solution risks proactively, grounding recommendations in realistic assessments of data, system readiness, and operational feasibility. * Evaluate, quantify, and communicate the business impact of deployed solutions using statistical and causal inference methods, ensuring benefit realization is measured rigorously and credibly. * Serve as a trusted advisor by effectively managing stakeholder expectations, influencing decision-making, and translating analytical outcomes into actionable business insights. * Drive cross-functional collaboration by working closely with engineering, product management, and business partners to ensure model deployment and adoption success. * Quantify business benefits from deployed solutions using rigorous statistical and causal inference methods, ensuring that model outcomes translate into measurable value * Design and implement robust, scalable solutions using Python, SQL, and PySpark on enterprise data platforms such as Databricks and GCP. * Contribute to the development of enterprise standards for reproducible research, model governance, and analytics quality. Who You Are * Master's or Ph.D. in Operations Research, Operations Management, Industrial Engineering, Applied Mathematics, or a closely related quantitative discipline. * 10+ years of experience developing, deploying, and scaling optimization and data science solutions in retail, supply chain, or similar complex domains. * Proven track record of delivering production-grade analytical solutions that have influenced business strategy and delivered measurable outcomes. * Strong expertise in operations research methods, including linear, nonlinear, and mixed-integer programming, stochastic modeling, and simulation. * Deep technical proficiency in Python, SQL, and PySpark, with experience in optimization and ML libraries such as Pyomo, Gurobi, OR-Tools, scikit-learn, and MLlib. * Hands-on experience with enterprise platforms such as Databricks and cloud environments * Demonstrated ability to assess, communicate, and mitigate risk across analytical, technical, and business dimensions. * Excellent communication and storytelling skills, with a proven ability to convey complex analytical concepts to technical and non-technical audiences. * Strong collaboration and influence skills, with experience leading cross-functional teams in matrixed organizations. * Experience managing code quality, CI/CD pipelines, and GitHub-based workflows. Preferred Qualifications * Experience shaping and executing multi-year analytics strategies in retail or supply chain domains. * Proven ability to balance long-term innovation with short-term deliverables. * Background in agile product development and stakeholder alignment for enterprise-scale initiatives. Benefits at Gap Inc. * Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees. * One of the most competitive Paid Time Off plans in the industry.* * Employees can take up to five "on the clock" hours each month to volunteer at a charity of their choice.* * Extensive 401(k) plan with company matching for contributions up to four percent of an employee's base pay.* * Employee stock purchase plan.* * Medical, dental, vision and life insurance.* * See more of the benefits we offer. * For eligible employees Gap Inc. is an equal-opportunity employer and is committed to providing a workplace free from harassment and discrimination. We are committed to recruiting, hiring, training and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We have received numerous awards for our long-held commitment to equality and will continue to foster a diverse and inclusive environment of belonging. In 2022, we were recognized by Forbes as one of the World's Best Employers and one of the Best Employers for Diversity. Salary Range: $201,700 - $267,300 USD Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable is seeking a product-focused Data Scientist to join our Analytics & Data Science team. In this high-impact role, you'll partner closely with product development teams to transform raw user data into actionable insights that drive growth for Airtable's self-serve business. You'll own critical data pipelines, design and analyze experiments, build dashboards, and deliver strategic insights that inform executive decision-making. This is a unique opportunity to shape the future of a data-driven, AI-native SaaS company and scale analytics best practices across the organization. What you'll do Own and maintain core product data pipelines across DBT, Looker, and Omni, ensuring reliability, scalability, and minimal downtime Build and refine dashboards that deliver self-serve, real-time insights for high-priority product areas Lead the development and delivery of company-wide strategic insights that connect user behavior patterns and inform executive decisions Partner with product and engineering teams to define tracking requirements, implement instrumentation, validate data, and deliver launch-specific dashboards or reports Establish trusted partnerships with product managers, engineers, analysts, and leadership as the go-to resource for product data insights and technical guidance Collaborate with leadership to define the analytics roadmap, prioritize high-impact initiatives, and assess resource needs for scaling product analytics capabilities Mentor junior team members and cross-functional partners on analytics best practices and data interpretation; create documentation and training materials to scale institutional knowledge Support end-to-end analytics for all product launches, including tracking implementation, validation, and post-launch reporting with documented impact measurements Deliver comprehensive strategic analyses or experiments that connect user behavior patterns and identify new growth opportunities Lead or participate in cross-functional projects where data science contributions directly influence product or strategy decisions Migrate engineering team dashboards to Omni or Databricks, enabling self-serve analytics Who you are Bachelor's degree in computer science, data science, mathematics/statistics, or related field 6+ years of experience as a data scientist, data analyst, or data engineer Experience supporting product development teams and driving product growth insight Background in SaaS, consumer tech, or data-driven product environments preferred Expert in SQL and modern data modeling (e.g., dbt, Databricks, Snowflake, BigQuery); sets standards and mentors others on best practices Deep experience with BI tools and modeling (e.g., Looker, Omni, Hex, Tableau, Mode) Proficient with experimentation platforms and statistical libraries (e.g., Eppo, Optimizely, LaunchDarkly, scipy, statsmodels) Proven ability to apply AI/ML tools - from core libraries (scikit-learn, PyTorch, TensorFlow) to GenAI platforms (ChatGPT, Claude, Gemini) and AI-assisted development (Cursor, GitHub Copilot) Strong statistical foundation; designs and scales experimentation practices that influence product strategy and culture Translates ambiguous business questions into structured analyses, guiding teams toward actionable insights Provides thought leadership on user funnels, retention, and growth analytics Ensures data quality, reliability, and consistency across critical business reporting and analytics workflows Experience at an AI-native company, with exposure to building or scaling products powered by AI Knowledge of product analytics tracking frameworks (e.g., Segment, Amplitude, Mixpanel, GA4) and expertise in event taxonomy design Strong documentation and knowledge-sharing skills; adept at creating technical guides, playbooks, and resources that scale team effectiveness Models curiosity, creativity, and a learner's mindset; thrives in ambiguity and inspires others to do the same Crafts compelling narratives with data, aligning stakeholders at all levels and driving clarity in decision-making Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or any characteristic protected by applicable federal and state laws, regulations and ordinances. Learn more about your EEO rights as an applicant. VEVRAA-Federal Contractor If you have a medical condition, disability, or religious belief/practice which inhibits your ability to participate in any part of the application or interview process, please complete our Accommodations Request Form and let us know how we may assist you. Airtable is committed to participating in the interactive process and providing reasonable accommodations to qualified applicants. Compensation awarded to successful candidates will vary based on their work location, relevant skills, and experience. Our total compensation package also includes the opportunity to receive benefits, restricted stock units, and may include incentive compensation. To learn more about our comprehensive benefit offerings, please check out Life at Airtable. For work locations in the San Francisco Bay Area, Seattle, New York City, and Los Angeles, the base salary range for this role is:$205,200-$266,300 USDFor all other work locations (including remote), the base salary range for this role is:$185,300-$240,000 USD Please see our Privacy Notice for details regarding Airtable's collection and use of personal information relating to the application and recruitment process by clicking here. 🔒 Stay Safe from Job Scams All official Airtable communication will come from an @airtable.com email address. We will never ask you to share sensitive information or purchase equipment during the hiring process. If in doubt, contact us at ***************. Learn more about avoiding job scams here.

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible. Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. At Pinterest, Shopping is a strategic initiative that aims to help Pinners take action by surfacing the most relevant content, at the right time, in the best user-friendly way. We do this through a combination of innovative product interfaces, and sophisticated recommendation systems. We are looking for a Staff Data Scientist with experience in machine learning and causal inference to help advance Shopping at Pinterest. In your role you will develop methods and models to explain why certain content is being promoted (or not) for a Pinner. You will work in a highly collaborative and cross-functional environment, and be responsible for partnering with Product Managers and Machine Learning Engineers. You are expected to develop a deep understanding of our recommendation system, and generate insights and robust methodologies to answer the "why". The results of your work will influence our development teams, and drive product innovation. What you'll do: * Ensure that our recommendation systems produce trustworthy, high-quality outputs to maximize our Pinner's shopping experience. * Develop robust frameworks, combining online and offline methods, to comprehensively understand the outputs of our recommendations. * Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners. * Work cross-functionally to build relationships, proactively communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest. * Relentlessly focus on impact, whether through influencing product strategy, advancing our north star metrics, or improving a critical process. * Mentor and up-level junior data scientists on the team. What we're looking for: * 7+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data. * Strong interest and experience in recommendation systems and causal inference. * Strong quantitative programming (Python/R) and data manipulation skills (SQL/Spark). * Ability to work independently and drive your own projects. * Excellent written and communication skills, and able to explain learnings to both technical and non-technical partners. * A team player eager to partner with cross-functional partners to quickly turn insights into actions. * Bachelor's/Master's degree in a relevant field such as Computer Science, or equivalent experience. In-Office Requirement Statement: * We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection. * This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. Relocation Statement: * This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. #LI-REMOTE #LI-NM4 At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only $164,695-$339,078 USD Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.

Our client is seeking a Data Engineer with hands-on experience in Web Scraping technologies to help build and scale a new scraping capability within their Data Engineering team. This role will work directly with Technology, Operations, and Compliance to source, structure, and deliver alternative data from websites, APIs, files, and internal systems. This is a unique opportunity to shape a new service offering and grow into a senior engineering role as the platform evolves. Responsibilities Develop scalable Web Scraping solutions using AI-assisted tools, Python frameworks, and modern scraping libraries. Manage the full lifecycle of scraping requests, including intake, feasibility assessment, site access evaluation, extraction approach, data storage, validation, entitlement, and ongoing monitoring. Coordinate with Compliance to review Terms of Use, secure approvals, and ensure all scrapes adhere to regulatory and internal policy guidelines. Build and support AWS-based data pipelines using tools such as Cron, Glue, EventBridge, Lambda, Python ETL, and Redshift. Normalize and standardize raw, vendor, and internal datasets for consistent consumption across the firm. Implement data quality checks and monitoring to ensure the reliability, historical continuity, and operational stability of scraped datasets. Provide operational support, troubleshoot issues, respond to inquiries about scrape behavior or data anomalies, and maintain strong communication with users. Promote data engineering best practices, including automation, documentation, repeatable workflows, and scalable design patterns. Required Qualifications Bachelor's degree in Computer Science, Engineering, Mathematics, or related field. 2-5 years of experience in a similar Data Engineering or Web Scraping role. Capital markets knowledge with familiarity across asset classes and experience supporting trading systems. Strong hands-on experience with AWS services (S3, Lambda, EventBridge, Cron, Glue, Redshift). Proficiency with modern Web Scraping frameworks (Scrapy, BeautifulSoup, Selenium, Playwright). Strong Python programming skills and experience with SQL and NoSQL databases. Familiarity with market data and time series datasets (Bloomberg, Refinitiv) is a plus. Experience with DevOps/IaC tooling such as Terraform or CloudFormation is desirable.