Data scientist jobs in Hillsdale, 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 ************ ********************

Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Ability to Obtain Public Trust About our AI and Data Capability Team Our consultants on the AI and Data Analytics Capability team help clients maximize the value of their data and automate business processes. This high performing team works with clients to implement the full spectrum of data analytics and data science services, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as intelligent automation. Our services enable our clients to define their information strategy, enable mission critical insights and data-driven decision making, reduce cost and complexity, increase trust, and improve operational effectiveness. What You Will Do: Data Collection & Management: Identify, gather, and manage data from primary and secondary sources, ensuring its accuracy and integrity. Data Cleaning & Preprocessing: Clean raw data by identifying and addressing inconsistencies, missing values, and errors to prepare it for analysis. Data Analysis & Interpretation: Apply statistical techniques and analytical methods to explore datasets, discover trends, find patterns, and derive insights. Data Visualization & Reporting: Develop reports, dashboards, and visualizations using tools like Tableau or Power BI to present complex findings clearly to stakeholders. Collaboration & Communication: Work with cross-functional teams, understand business requirements, and effectively communicate insights to support data-driven decision-making. Problem Solving: Address specific business challenges by using data to identify underperforming processes, pinpoint areas for growth, and determine optimal strategies. What You Will Need: US Citizenship is required Bachelor's degree is required Minimum THREE (3) Years Experience using Power BI, Tableau and other visualization tools to develop intuitive and user friendly dashboards and visualizations. Skilled in SQL, R, and other languages to assist in database querying and statistical programming. Strong foundational knowledge and experience in statistics, probability, and experimental design. Familiarity with cloud platforms (e.g., Amazon Web Services, Azure, or Google Cloud) and containerization (e.g., Docker). Experience applying data governance concepts and techniques to assure greater data quality and reliability. he curiosity and creativity to uncover hidden patterns and opportunities. Strong communication skills to bridge technical and business worlds. What Would Be Nice To Have: Hands-on experience with Python, SQL, and modern ML frameworks. Experience in data and AI system development, with a proven ability to design scalable architectures and implement reliable models. Expertise in Python or Java for data processing. Demonstrated work experience within the public sector. Ability to support business development including RFP/RFQ/RFI responses involving data science / analytics. #LI-DNI The annual salary range for this position is $113,000.00-$188,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity EmployerProtected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at ************** or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or ************************. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouses Ethics Hotline. If you want to check the validity of correspondence you have received, please contact *************************. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicants dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Data Scientist- Parsippany, NJ (Hybrid) Data Scientist Summary: Provide analytics, telemetry, ML/GenAI-driven insights to measure SDLC health, prioritize improvements, validate pilot outcomes, and implement AI-driven development lifecycle capabilities. • Responsibilities: o Define metrics and instrumentation for SDLC/CI pipelines, incidents, and delivery KPIs. o Build dashboards, anomaly detection, and data models; implement GenAI solutions (e.g., code suggestion, PR summarization, automated test generation) to improve developer workflows. o Design experiments and validate AI-driven features during the pilot. o Collaborate with engineering and SRE to operationalize models and ensure observability and data governance. • Required skills: o Applied data science/ML in production; hands-on experience with GenAI/LLMs applied to developer workflows or DevOps automation. o Strong Python (pandas, scikit-learn), ML frameworks, SQL, and data visualization (Tableau/Power BI). o Experience with observability/telemetry data (logs/metrics/traces) and A/B experiment design. • Preferred: o Experience with model deployment, MLOps, prompt engineering, and cloud data platforms (AWS/GCP/Azure).

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

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.

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 *****************************

About the Opportunity Our client is a global alternative investment firm in a high-growth phase, investing heavily in modernizing its enterprise data platform. With multiple investment strategies and operations across several geographies, the firm is building a scalable, front-to-back investment data environment to support portfolio management, performance reporting, and executive decision-making. This is a hands-on, senior individual contributor role for an engineer who has worked close to investment teams and understands financial and portfolio data, not just generic SaaS analytics. Who This Role Is For This role is ideal for data engineers who have experience in or alongside Private Equity, Hedge Funds, Asset Management, or Capital Markets environments and are comfortable owning complex financial data pipelines end-to-end. This is not a traditional BI, marketing, or consumer data role. Candidates coming purely from ad-tech, healthcare, or non-financial SaaS backgrounds may not find this a fit. What You'll Be Doing Design, build, and maintain scalable data pipelines supporting investment, portfolio, and fund-level data Partner closely with technology leadership and investment stakeholders to translate business and investment use cases into technical solutions Contribute to the buildout of a modern data lake / lakehouse architecture (medallion-style or similar) Integrate data across the full investment lifecycle, including: Deal and transaction data Portfolio company metrics Fund performance, AUM, and reporting data Ensure data quality, lineage, and reliability across multiple strategies and entities Operate as a senior, hands-on engineer - designing, building, and troubleshooting in the weeds when needed Required Experience 7+ years of experience as a Data Engineer or similar role Strong background supporting financial services data, ideally within: Private Equity Hedge Funds Asset Management Investment Banking / Capital Markets Experience working with complex, multi-entity datasets tied to investments, portfolios, or funds Strong SQL skills and experience building production-grade data pipelines Experience with modern cloud data platforms and architectures Comfortable working in a fast-moving, evolving environment with senior stakeholders Nice to Have Experience in environments similar to global PE firms, hedge funds, or institutional asset managers Exposure to front-to-back investment data (from source systems through reporting) Experience with Microsoft-centric data stacks (e.g., Azure, Fabric) or comparable cloud platforms Familiarity with performance, valuation, or risk-related datasets Work Environment & Compensation Hybrid role with regular collaboration in the New York office Competitive compensation aligned with senior financial services engineering talent Opportunity to help shape a firm-wide data platform during a critical growth phase

🚀 Market Data Engineer - New York | Cutting-Edge Trading Environment I'm partnered with a leading technology-driven trading team in New York looking to bring on a Market Data Engineer to support global research, trading, and infrastructure groups. This role is central to managing the capture, normalization, and distribution of massive volumes of historical market data from exchanges worldwide. What You'll Do Own large-scale, time-sensitive market data capture + normalization pipelines Improve internal data formats and downstream datasets used by research and quantitative teams Partner closely with infrastructure to ensure reliability of packet-capture systems Build robust validation, QA, and monitoring frameworks for new market data sources Provide production support, troubleshoot issues, and drive quick, effective resolutions What You Bring Experience building or maintaining large-scale ETL pipelines Strong proficiency in Python + Bash, with familiarity in C++ Solid understanding of networking fundamentals Experience with workflow/orchestration tools (Airflow, Luigi, Dagster) Exposure to distributed computing frameworks (Slurm, Celery, HTCondor, etc.) Bonus Skills Experience working with binary market data protocols (ITCH, MDP3, etc.) Understanding of high-performance filesystems and columnar storage formats

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.

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.

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.

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.

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 seeking a C++ Market Data Engineer to design and optimize ultra-low-latency feed handlers that power global trading systems. This is a high-impact role where your code directly drives real-time decision making. What You'll Do: Build high-performance feed handlers in modern C++ (14/17/20) for equities, futures, and options Optimize systems for micro/nanosecond latency with lock-free algorithms and cache-friendly design Ensure reliable data delivery with failover, gap recovery, and replay mechanisms Collaborate with researchers and engineers to align data formats for trading and simulation Instrument and test systems for continuous performance improvements What We're Looking For: 3+ years of C++ development experience (low-latency, high-throughput systems) Experience with real-time market data feeds (e.g., Bloomberg B-PIPE, CME MDP, Refinitiv, OPRA, ITCH) Strong knowledge of concurrency, memory models, and compiler optimizations Python scripting skills for testing and automation Familiarity with Docker/Kubernetes and cloud networking (AWS/GCP) is a plus

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.

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

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).

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).