Data engineer jobs in Levittown, NY

Our client is a $28B NY based multi-strategy Hedge Fund currently seeking to add a talented Associate to their Data & Performance Analytics Team. This individual will be working closely with senior managers across finance, investment management, operations, technology, investor services, compliance/legal, and marketing. Responsibilities This role will be responsible for Compiling periodical fund performance analyses Review and analyze portfolio performance data, benchmark performance and risk statistics Review and make necessary adjustments to client quarterly reports to ensure reports are sent out in a timely manner Work with all levels of team members across the organization to help coordinate data feeds for various internal and external databases, in effort to ensure the integrity and consistency of portfolio data reported across client reporting systems Apply queries, pivot tables, filters and other tools to analyze data. Maintain client relationship management database and providing reports to Directors on a regular basis Coordinate submissions of RFPs by working with RFP/Marketing Team and other groups internally to gather information for accurate data and performance analysis Identifying opportunities to enhance the strategic reporting platform by gathering and analyzing field feedback and collaborating with partners across the organization Provide various ad hoc data research and analysis as needed. Desired Skills and Experience Bachelor's Degree with at least 2+ years of Financial Services/Private Equity data/client reporting experience Proficiency in Microsoft Office, particularly Excel Modeling Technical knowledge, data analytics using CRMs (Salesforce), Excel, PowerPoint Outstanding communication skills, proven ability to effectively work with all levels of Managment Comfortable working in a fast-paced, dead-line driven dynamic environment Innovative and creative thinker Must be detail oriented

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

Avanciers is seeking to hire few Sr. Data Engineers in Jersey City, NJ area, for one of its esteemed client. Candidates can apply directly through the job description ASAP: Mandatory Skills: Python, scripting, web services, api design, etc. Kubernetes CI/CD (preferably gitlab) Job Orchestration (preferably Airflow) Familiarity with Snowflake (doesn't need to be an expert) Nice to have: Azure DBT AI automation experience Financial services experience

required ) About the job: We're seeking a Lead Data Engineer to drive innovation and excellence across our Marketing Technology data ecosystem. You thrive in dynamic, fast-paced environments and are comfortable navigating both legacy systems and modern data architectures. You balance long-term strategic planning with short-term urgency, responding to challenges with clarity, speed, and purpose. You take initiative, quickly familiarize yourself with source systems, ingestion pipelines, and operational processes, and integrate seamlessly into agile work rhythms. Above all, you bring a solution-oriented, win-win mindset-owning outcomes and driving progress. What you will do at Sogeti: Rapidly onboard into our Martech data ecosystem-understanding source systems, ingestion flows, and operational processes. Build and maintain scalable data pipelines across Martech, Loyalty, and Engineering teams. Balance long-term projects with short-term reactive tasks, including urgent bug fixes and business-critical issues. Identify gaps in data infrastructure or workflows and proactively propose and implement solutions. Collaborate with product managers, analysts, and data scientists to ensure data availability and quality. Participate in agile ceremonies and contribute to backlog grooming, sprint planning, and team reviews. What you will bring: 7+ years of experience in data engineering, with a strong foundation in ETL design, cloud platforms, and real-time data processing. Deep expertise in Snowflake, Airflow, dbt, Fivetran, AWS S3, Lambda, Python, SQL. Previous experience integrating data from multiple retail and ecommerce source systems. Experience with implementation and data management for loyalty platforms, customer data platforms, marketing automation systems, and ESPs. Deep expertise in data modeling with dbt. Demonstrated ability to lead critical and complex platform migrations and new deployments. Strong communication and stakeholder management skills. Self-driven, adaptable, and proactive problem solver Education: Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, Business Administration, or a related field. Life at Sogeti: Sogeti supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer: Flexible work options 401(k) with 150% match up to 6% Employee Share Ownership Plan Medical, Prescription, Dental & Vision Insurance Life Insurance 100% Company-Paid Mobile Phone Plan 3 Weeks PTO + 7 Paid Holidays Paid Parental Leave Adoption, Surrogacy & Cryopreservation Assistance Subsidized Back-up Child/Elder Care & Tutoring Career Planning & Coaching $5,250 Tuition Reimbursement & 20,000+ Online Courses Employee Resource Groups Counseling & Support for Physical, Financial, Emotional & Spiritual Well-being Disaster Relief Programs About Sogeti Part of the Capgemini Group, Sogeti makes business value through technology for organizations that need to implement innovation at speed and want a local partner with global scale. With a hands-on culture and close proximity to its clients, Sogeti implements solutions that will help organizations work faster, better, and smarter. By combining its agility and speed of implementation through a DevOps approach, Sogeti delivers innovative solutions in quality engineering, cloud and application development, all driven by AI, data and automation. Become Your Best | ************* Disclaimer Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant ************************************************************************** Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini. Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future. The disclosed range takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, performance, sales or revenue-based metrics, and business or organizational needs. At Capgemini, it is not typical for an individual to be hired at or near the top of the range for their role. The base salary range for the tagged location is $125,000 - $175,000. This role may be eligible for other compensation including variable compensation, bonus, or commission. Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.

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.

🚀 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

We are seeking a Lead Data Engineer to design, build, and scale our enterprise data platform supporting analytics, reporting, and investment decision-making across asset classes. This role combines technical leadership with hands-on development, focusing on data architecture, pipeline design, and governance for high-quality, reliable financial data. You will be acting as a liaison between business stakeholders and the engineering team. Responsibilities: Lead the design and implementation of modern data pipelines and ETL/ELT frameworks using cloud and on-prem environments. Architect and manage data models, warehouses, and lakehouses to support analytics, reporting, and machine learning. Collaborate with investment, risk, and technology teams to define data requirements and ensure consistency across systems. Drive best practices in data quality, lineage, and governance. Mentor engineers and set standards for performance, security, and scalability. Evaluate and implement new data technologies to improve efficiency and insights delivery. Qualifications: 7+ years of experience in data engineering, with 2+ in a technical leadership role. Strong expertise in SQL, Python, and modern data platforms (e.g., Azure Data Factory, Databricks, Snowflake, Synapse, AWS Glue, or GCP BigQuery). Experience with data modeling, ETL/ELT pipelines, and data warehousing principles. Familiarity with financial or investment data (portfolio, risk, performance, or accounting) preferred. Strong understanding of CI/CD, version control (Git), and DevOps for data workflows. Excellent communication and cross-functional collaboration skills.

About Beauty by Imagination: Beauty by Imagination is a global haircare company dedicated to boosting self-confidence with imaginative solutions for every hair moment. We are a platform company of diverse, market-leading brands, including Wet Brush, Goody, Bio Ionic, and Ouidad - all of which are driven to be the most trusted choice for happy, healthy hair. Our talented team is passionate about delivering high-performing products for consumers and salon professionals alike. Position Overview: We are looking for a skilled Data Engineer to design, build, and maintain our enterprise Data Warehouse (DWH) and analytics ecosystem - with a growing focus on enabling AI-driven insights, automation, and enterprise-grade AI usage. In this role, you will architect scalable pipelines, improve data quality and reliability, and help lay the foundational data structures that power tools like Microsoft Copilot, Copilot for Power BI, and AI-assisted analytics across the business. You'll collaborate with business stakeholders, analysts, and IT teams to modernize our data environment, integrate complex data sources, and support advanced analytics initiatives. Your work will directly influence decision-making, enterprise reporting, and next-generation AI capabilities built on top of our Data Warehouse. Key Responsibilities Design, develop, and maintain Data Warehouse architecture, including ETL/ELT pipelines, staging layers, and data marts. Build and manage ETL workflows using SQL Server Integration Services (SSIS) and other data integration tools. Integrate and transform data from multiple systems, including ERP platforms such as NetSuite. Develop and optimize SQL scripts, stored procedures, and data transformations for performance and scalability. Support and enhance Power BI dashboards and other BI/reporting systems. Implement data quality checks, automation, and process monitoring. Collaborate with business and analytics teams to translate requirements into scalable data solutions. Contribute to data governance, standardization, and documentation practices. Support emerging AI initiatives by ensuring model-ready data quality, accessibility, and semantic alignment with Copilot and other AI tools. Required Qualifications Proven experience with Data Warehouse design and development (ETL/ELT, star schema, SCD, staging, data marts). Hands-on experience with SSIS (SQL Server Integration Services) for building and managing ETL workflows. Strong SQL skills and experience with Microsoft SQL Server. Proficiency in Power BI or other BI tools (Tableau, Looker, Qlik). Understanding of data modeling, performance optimization, and relational database design. Familiarity with Python, Airflow, or Azure Data Factory for data orchestration and automation. Excellent analytical and communication skills. Preferred Qualifications Experience with cloud data platforms (Azure, AWS, or GCP). Understanding of data security, governance, and compliance (GDPR, SOC2). Experience with API integrations and real-time data ingestion. Background in finance, supply chain, or e-commerce analytics. Experience with NetSuite ERP or other ERP systems (SAP, Oracle, Dynamics, etc.). AI Focused Preferred Skills: Experience implementing AI-driven analytics or automation inside Data Warehouses. Hands-on experience using Microsoft Copilot, Copilot for Power BI, or Copilot Studio to accelerate SQL, DAX, data modeling, documentation, or insights. Familiarity with building RAG (Retrieval-Augmented Generation) or AI-assisted query patterns using SQL Server, Synapse, or Azure SQL. Understanding of how LLMs interact with enterprise data, including grounding, semantic models, and data security considerations (Purview, RBAC). Experience using AI tools to optimize ETL/ELT workflows, generate SQL scripts, or streamline data mapping/design. Exposure to AI-driven data quality monitoring, anomaly detection, or pipeline validation tools. Experience with Microsoft Fabric, semantic models, or ML-integrated analytics environments. Soft Skills Strong analytical and problem-solving mindset. Ability to communicate complex technical concepts to business stakeholders. Detail-oriented, organized, and self-motivated. Collaborative team player with a growth mindset. Impact You will play a key role in shaping the company's modern data infrastructure - building scalable pipelines, enabling advanced analytics, and empowering the organization to safely and effectively adopt AI-powered insights across all business functions. Our Tech Stack SQL Server, SSIS, Azure Synapse Python, Airflow, Azure Data Factory Power BI, NetSuite ERP, REST APIs CI/CD (Azure DevOps, GitHub) What We Offer Location: New York, NY (Hybrid work model) Employment Type: Full-time Compensation: Competitive salary based on experience Benefits: Health insurance, 401(k), paid time off Opportunities for professional growth and participation in enterprise AI modernization initiatives

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

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).

· 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 *****************************

Industry: Retail Salary: $150,000-$175,000 + Bonus Contact: ******************************** Our client is a prominent player in the Apparel sector, committed to fusing fashion with cutting-edge data and technological solutions. Situated in New York, this organization is on the lookout for a Data Science Manager to drive their Operations Intelligence initiatives within the Data & Analytics department. This critical role is pivotal in leveraging advanced analytics, predictive modeling, and state-of-the-art Generative AI technologies to bolster decision-making across key operational areas such as Planning, Supply Chain, Sourcing, Sales, and Logistics. The selected candidate will oversee the integration of data science methodologies into essential operational workflows, aiming to automate processes, improve visibility, accurately forecast business dynamics, and facilitate strategic planning through insightful data analysis. Requirements A minimum of 6 years of experience in the field of data science, with at least 2 years in a leadership or product-related role. Proven ability to apply analytics in complex operational environments such as planning, supply chain, and sourcing. Strong expertise in Python and SQL, along with a solid grasp of cloud-based data ecosystems. Experience with advanced modeling techniques, including forecasting, optimization, and classification. Familiarity with Generative AI technologies or LLMs, combined with a keen interest in leveraging these for practical business applications. Excellent business acumen and communication skills, facilitating effective collaboration between data insights and strategic goals.

Immediate need for a talented Data Architect. This is a 12 month contract opportunity with long-term potential and is located in Basking Ridge, NJ (Hybrid). Please review the job description below and contact me ASAP if you are interested. Job ID:25-93859 Pay Range: $110 - $120/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location). Key Requirements and Technology Experience: Key Skills; ETL, LTMC, SaaS . 5 years as a Data Architect 5 years in ETL 3 years in LTMC Our client is a leading Telecom Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration. Pyramid Consulting, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails from Pyramid Consulting, Inc. and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here.

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.

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

Hi, I hope you are doing well! We have an opportunity for Data Architect with one of our clients for NYC, NY. Please see the job details below and let me know if you would be interested in this role. If interested, please send me a copy of your resume, contact details, availability, and a good time to connect with you. Title: Data Architect Location: New York, New York - Onsite Terms: Long Term Contract Job Details: Primary Skills: SQL,ORACLE,Snowflake,12+ years of experience in data technology At least 5 years as a Data Engineer with hands-on experience in cloud environments 8+ years of Python programming focused on data processing and distributed systems 8+ years working with relational databases, dimensional modeling, and DBT 8+ years designing and administering cloud-based data warehousing solutions (e.g., Databricks) 8+ years' experience with Kafka or other streaming platforms Exposure to AI based advance techniques and tools Strong understanding of database fundamentals, including data modeling, advanced SQL development and optimization, ELT/ETL processes and DBT. Experience with Java, MS SQL Server, Druid, Qlik/Golden Gate CDC, and Power BI is a plus Responsibilities: Architect streaming data ingestion and integration with downstream systems Implement AI-driven controller to orchestrate tens of millions of streams and micro-batches Design AI-powered onboarding of new data sources Develop AI-powered compute engine and data serving semantic layer Deliver scalable cloud data services and APIs with sub-second response times over petabytes of data Develop a unified alerting and monitoring framework supporting streaming transformations and compute across thousands of institutional clients and hundreds of external data sources Build a self-service data management and operations platform Implement a data quality monitoring framework Qualifications: Bachelor's degree in Computer Science, related field; advanced degree preferred 12+ years of experience in data technology At least 5 years as a Data Engineer with hands-on experience in cloud environments 8+ years of Python programming focused on data processing and distributed systems 8+ years working with relational databases, SQL, dimensional modeling, and DBT 8+ years designing and administering cloud-based data warehousing solutions (e.g., Snowflake, Databricks) 8+ years experience with Kafka or other streaming platforms Exposure to AI based advance techniques and tools Strong understanding of database fundamentals, including data modeling, advanced SQL development and optimization, ELT/ETL processes and DBT. Experience with Java, Oracle, MS SQL Server, Druid, Qlik/Golden Gate CDC, and Power BI is a plus Strong leadership abilities and excellent communication skills. Thanks Amit Jha Senior Recruiter at BeaconFire Inc. Email : ***********************

# Job Description: AI Task Evaluation & Statistical Analysis Specialist ## Role Overview We're seeking a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). ## Key Responsibilities - **Statistical Failure Analysis**: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - **Root Cause Analysis**: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations - **Dimension Analysis**: Analyze performance variations across finance sub-domains, file types, and task categories - **Reporting & Visualization**: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities - **Quality Framework**: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings - **Stakeholder Communication**: Present insights to data labeling experts and technical teams ## Required Qualifications - **Statistical Expertise**: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition - **Programming**: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis - **Data Analysis**: Experience with exploratory data analysis and creating actionable insights from complex datasets - **AI/ML Familiarity**: Understanding of LLM evaluation methods and quality metrics - **Tools**: Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL ## Preferred Qualifications - Experience with AI/ML model evaluation or quality assurance - Background in finance or willingness to learn finance domain concepts - Experience with multi-dimensional failure analysis - Familiarity with benchmark datasets and evaluation frameworks - 2-4 years of relevant experience

Must Have Technical/Functional Skills • Deep understanding of Financial Crime Risk Management (FCRM): AML, KYC, Sanctions Screening, Transaction Monitoring, Fraud Detection • Experience designing data solutions for risk scoring, suspicious activity reporting, and regulatory audits • Advanced knowledge of: Data governance and data management practices Enterprise data policy, standards & strategy M&A due diligence process Line of Business (LOB) data strategy Data risk management and data life cycle management • Experience with scalable data mesh architectures on Azure Azure Data Factory Databricks • Strong analytical skills using software tools and reporting techniques • Familiarity with regulatory frameworks: FATF, FINTRAC, OFAC (good to have) • Knowledge of FCRM data models and case management workflows (good to have) • Integration of data from core banking, payment, and customer systems (good to have) • 10+ years of relevant experience Roles & Responsibilities • Design and implement scalable data mesh architectures • Define data domains, schemas, and integration patterns • Support FCRM processes and regulatory compliance through data solutions • Mentor and coach team members • Contribute to strategic direction and advise senior leadership • Ensure data solutions align with internal controls and regulatory reporting • Document issues/findings and monitor lifecycle • Develop procedures and document processes • Perform risk assessments and support operational risk management • Conduct user training and provide support to Tableau users. Interested candidates please share me your updated resume to ******************* Salary Range- $130,000-$150,000 a year TCS Employee Benefits Summary: Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.< /span> Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Designing Hive/HCatalog data model includes creating table definitions, file formats, compression techniques for Structured & Semi-structured data processing Implementing Spark processing based ETL frameworks Implementing Big data pipeline for Data Ingestion, Storage, Processing & Consumption Modifying the Informatica-Teradata & Unix based data pipeline Enhancing the Talend-Hive/Spark & Unix based data pipelines Develop and Deploy Scala/Python based Spark Jobs for ETL processing Strong SQL & DWH concepts