Data Engineer

• Lead and grow a team of data engineers, providing mentorship and leadership within the function
• Build the future of the data engineering practice to deliver value to internal and external stakeholders while leveraging cutting edge technologies to dramatically accelerate quality, scale, and depth of delivery
• Design and implement scalable data pipelines to collect, process, and store large volumes of critical data from various sources
• Drive the evolution of the Business Data platform by leveraging modern data technologies like Spark, Airflow, and Databricks
• Collaborate across organizational boundaries with Product, Marketing, and Sales to convert business needs into technical requirements
• Authoritatively translate business use cases into well-thought-out data models that evolve with the business

Director, Data Engineering – Business Data

• Design, build, and maintain scalable data pipelines across internal databases, vendor systems, and our data warehouse
• Support both batch and event-driven or CDC-based data workflows
• Improve pipeline reliability, observability, and performance
• Troubleshoot issues in production and proactively solve data quality or system problems
• Build and maintain data warehouse schemas and transformation layers to support analytics and operational use cases
• Communicate clearly about implementation choices, tradeoffs, and technical constraints
• Identify opportunities to improve data workflows through better tooling, automation, and engineering practices
• Help shape scalable patterns for how data is ingested, transformed, stored, and accessed

Senior Data Engineer

• Designing and implementing AI systems to transform raw data into actionable insights
• Developing scalable machine learning models to support client decision-making processes
• Collaborating with cross-functional teams to integrate AI solutions into existing platforms
• Conducting data wrangling and preprocessing to prepare datasets for analysis
• Applying advanced algorithms to enhance the performance of AI models
• Building and deploying software systems that leverage AI and machine learning technologies
• Analyzing complex data sets to identify patterns and trends that inform business strategies
• Supporting client engagements by delivering quality work and adapting to diverse project requirements
• Engaging in continuous learning to deepen technical skills and knowledge in AI engineering
• Upholding professional and technical standards while contributing to team success

AI Engineer, AI Experienced Associate

• Design, build, and maintain scalable ingestion pipelines for market, reference, tick, and alternative data from a diverse set of external vendors.
• Own the normalization, validation, storage, and lifecycle management of research datasets, ensuring data is accurate, consistent, and readily accessible for quantitative research and simulation.
• Develop and optimize Python- and SQL-based data processing workflows supporting multiple asset classes, including equities, options, futures, fixed income, ETFs, and FX.
• Partner with quantitative researchers, data architects, and infrastructure teams to onboard new datasets, improve data quality, and deliver reliable research-ready data.
• Build monitoring, automation, and operational tooling to ensure the reliability, performance, and scalability of the firm's data platform.
• Document data pipelines and engineering best practices while contributing to the ongoing evolution of Trexquant's research data infrastructure.

• Lead a team of 2-3 engineers
• Working with fellow Nava engineers to design, review, and build well-crafted software
• Working in an agile manner to efficiently ship new features that meet user needs
• Design and develop scalable data ingestion and processing pipelines
• Implement large-scale data ecosystems within cloud-based platforms that include data management and data governance of structured and unstructured data
• Implement data validation and quality checks to ensure accuracy and consistency
• Work with cross-functional project teams to gather business requirements and translate to detailed technical specifications
• Work with Government partners to assist and develop data engineering applications and pipelines that will enable data services and processing capabilities
• Participate in software design and code reviews
• Maintain security and privacy standards in all aspects of the data pipeline
• Taking part in hiring activities (e.g., submitting referrals, conducting interviews, and attending interview debriefs), as needed

Senior Software Engineer, Data

• Design and build ETL/ELT data pipelines to ingest, process, and transform large datasets from multiple sources
• Implement best practices for performance tuning, partitioning, and clustering to optimize data queries and reduce costs
• Establish and enforce data quality standards, data governance frameworks, and security policies for data storage and access
• Develop and optimize data models and schemas to support analytics, reporting, and machine learning requirements
• Collaborate with data scientists and analysts to design data solutions that integrate with BI tools and machine learning models
• Create comprehensive documentation for data pipelines, workflows, and processes
• Share best practices and mentor junior data engineers

• Build and optimize analytical data models in BigQuery.
• Implement partitioning, clustering, and materialized views for performance and cost efficiency.
• Ensure compliance with data governance, access controls, and IAM best practices.
• Develop integrations with external systems (APIs, flat files etc.) using GCP-native or hybrid approaches.
• Utilize tools like Dataflow or custom Python/Java services on Cloud Functions or Cloud Run to handle transformations and ingestion logic.
• Build automated CI/CD pipeline using Cloud Build, GitHub Actions, or Jenkins for deploying data pipeline code and workflows.
• Set up observability using Cloud Monitoring, Cloud Logging, and Error Reporting to ensure pipeline reliability.

• Develop and implement object-oriented code and scripting languages to support the interface and accounting systems
• Implement solutions that enhance, streamline and automate the management of our IT systems
• Assist with the configuration, implementation and maintenance of the technical environments for the current development, staging and production environments
• Code and maintain system interfaces and extracts to handle the migration accounting information to ancillary systems
• Develop technical and functional test plans and scripts to validate the successful design, development, and implementation of system and reporting deliverables
• Code and support multiple in-place programs (Coordinate with project, support, and business analysts to develop functional and technical requirements, as well as translate detailed specifications into new or enhanced software solutions.)
• Assist with performance management and load/stress testing for the interface and accounting systems, as well as create interfaces and load-scripts to ancillary financial and reporting systems
• Manage the day-to-day operation and coordination of interface and accounting systems processes and enhancements
• Monitor process metrics and lead process improvement efforts
• Manage processing and enhancements for accounting feeds
• Support the Genworth Investments functions by troubleshooting and identify root cause analysis of application problems. Identify action items and make recommendations to address process and coding issues.
• Create and maintain derivatives support knowledge base that includes technical and process documentation.
• Some travel may be required (<15%) between Genworth's Richmond and Stamford locations

• Design and implement the canonical data model for Vultr’s control plane ERP transformation: product catalog, chart of accounts, financial transactions, cost centers
• Build and maintain the internal APIs and event streams that Finance, Analytics, and downstream systems consume
• Refactor existing administer code toward clean domain boundaries (no more conflated orders/ledger/report tables)
• Implement data upgrade/migration paths from legacy schemas without breaking production
• Write the integration layer between administer and Vultr's existing billing, provisioning, and reporting systems
• Establish data validation and integrity checks across the financial data layer
• Collaborate with the Product Manager to translate finance domain requirements into durable schema designs
• Document architectural decisions and data model contracts for downstream consumers

Senior Software Engineer, ERP, Data & Domain

• Finds trends in datasets and develops workflows and algorithms to make raw data useful to the enterprise
• Designs and implements standardized data management procedures around data staging, data ingestion, data preparation, data provisioning, and data destruction (scripts, programs, automation, assisted by automation, etc.)
• Ensures quality of technical solutions as data moves across Healthfirst environments
• Provides insight into the changing data environment, data processing, data storage and utilization requirements for the company and offers suggestions for solutions
• Ensures managed analytic assets support Healthfirst’s strategic goals by creating and verifying data acquisition requirements and strategy
• Develops, constructs, tests and maintains architectures
• Aligns architecture with business requirements and uses programming language and tools
• Identifies ways to improve data reliability, efficiency, and quality
• Conducts research for industry and business questions
• Deploys sophisticated analytics programs, machine learning and statistical methods
• Prepares data for predictive and prescriptive modeling and finds hidden patterns using data
• Uses data to discover tasks that can be automated
• Creates data monitoring capabilities for each business process and works with data consumers on updates
• Aligns data architecture to Healthfirst solution architecture; contributes to overall solution architecture
• Helps maintain the integrity and security of the company data

Healthcare Claims, Data Engineer

• Lead the strategy and execution of complex and large Data and Analytics portfolio.
• Develop and implement a strategic roadmap to modernize legacy data and analytics ecosystems using Cloud and AI.
• Ensure data architecture and solutions align with enterprise-wide standards for Data, AI and Analytics.
• AI Data Engineering leader responsible for Implementing AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions.
• Design, build and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery.
• Oversee the design, development, and maintenance of lakehouse architectures, data pipelines, data warehouses, data lakes and reporting systems.
• Mentor and lead a high-performing team including Directors, Business data analysts, Data engineers and Release train engineers.
• Identify and champion developer productivity improvements across the end-to-end data management lifecycle.

Director, Data Architect

• The intent of this position is to provide our internal employees, 2026 Travelers Summer Interns and Summer Students the ability to apply to our 2027 Full-time or Intern opportunities.
• Innovative thinking, creative problem-solving, and a determination to challenge the status-quo, these are some of the defining qualities for participants of our Engineering Development Program (EDP).
• The EDP is a one-year program where you will be placed in one of the four designated Engineering tracks: Software, Data, Cybersecurity or Infrastructure & Cloud.
• Each track is designed to grow and develop your technical and self-leadership skills.
• Within your assigned track, you will receive a combination of hands-on opportunities, an immersive learning journey, and a mentoring program to prepare you for a dynamic career.
• EDP Participants in this track will partner closely with the business to refine features, plan user stories, and execute on the analysis, design, development, and testing of those user stories to deliver business capabilities to market.
• Additional program components include mentoring, networking, and career guidance.
• Please note that occasional travel for business meetings and events is an expectation of program participants.
• Perform other duties as assigned.

Engineering Development Program – Data Engineering

• Lead the roadmap, sustainment, and modernization strategy for D360 and RIF.
• Ensure these platforms continue to meet critical business needs across discovery and preclinical research.
• Lead a cross-functional team responsible for platform delivery, support, data operations, and engineering coordination.
• Oversee delivery across internal teams and external partners supporting sustainment and transformation work.
• Partner across the Molecules & Assays Solutions portfolio along with key business stakeholders across Research Units and Partner Lines.
• Drive accountability for data quality, lineage, usability, and trust across scientific data flows.
• Work closely with scientific users, product leaders, business analysts, and technical teams to prioritize the highest-value improvements.

Director, Scientific Data Platforms Lead

• Design and implement data models across relational, graph, and lakehouse systems using AWS RDS, AWS Neptune, and Databricks
• Develop warehouse/lakehouse schemas in Databricks Delta Lake for analytics and ML
• Implement graph-based retrieval and integrate with vector search for AI use cases
• Generate embeddings and manage hybrid retrieval pipelines (graph + vector)
• Build ETL/ELT workflows using Databricks (PySpark), Airflow, or AWS Glue
• Ensure data quality, consistency, and freshness across systems
• Tune queries and optimize storage for Neptune, RDS, and Delta Lake
• Work with data scientists and AI engineers to support knowledge graph and RAG workflows
• Document data models and maintain governance standards

IAM IGA Data Engineer, Assistant Vice President

• Build and operationalize complex data solutions, correct problems, apply transformations, and recommending data cleansing/quality solutions.
• Design complex data solutions.
• Perform analysis of complex sources to determine value and use and recommend data to include in analytical processes.
• Incorporate core data management competencies including data governance, data security and data quality.
• Collaborate within and across teams to support delivery and educate end users on complex data products/analytic environment.
• Perform data and system analysis, assessment and resolution for complex defects and incidents and correct as appropriate.
• Test data movement, transformation code, and data components.
• Perform other duties as assigned.

Data Engineer II

• Solving our unique data-lake challenges: transforming and seamlessly normalizing highly varied partner datasets (such as donation data);
• Design robust batch-processing pipelines capable of extracting and loading massive datasets from a variety of internal, external, and public sources;
• Developing processes for data mining, data modeling, and data production;
• Leveraging modern technology knowledge to champion evolving industry trends, updated design patterns, and engineering excellence across the team;
• Autonomously scope, design, and execute complex data projects from day one, turning ambiguous requirements into clear, decisive technical plans;
• Developing robust testing and monitoring systems for scheduled processes;
• Collaborating with cross-functional teams to support their data infrastructure needs;
• Joining each and every one of your colleagues in creating an inclusive workspace.

Staff Data Engineer

• drive the strategy and delivery of scalable, high-impact technology solutions supporting healthcare providers
• partner across product and engineering to deliver enterprise provider data transformation, modernization and engineering excellence across mission-critical platforms

Lead Director – Provider Data Engineering, Transformation

• Lead a distributed engineering team across platform/product engineering, connectors, QA, DevOps/infra, AI implementation, data governance, and support.
• Own delivery, quality, release discipline, and execution of the technical roadmap.
• Install engineering discipline where it's thin: automated testing, QA, CI/CD, release governance, and versioning.
• Drive repeatable, perimeter-safe deployments, including containerization, infrastructure-as-code, secure deployment, and SOC 2 readiness.
• Partner with the Chief Architect on the connector framework, canonical metadata model, architecture decisions, and product IP.
• Build the team: assess current talent, retain the strong, hire the gaps, and align the team plan to the roadmap.
• Push practical AI use across coding, review, testing, ops, and engineering productivity.

Director of Engineering – Data Platform

• Lead the design and evolution of Foley’s enterprise data architecture
• Contribute to the ongoing development of our Enterprise Data Model
• Define standards and best practices for data modeling, storage, access, and reliability
• Drive architectural decisions that balance scalability, maintainability, and performance
• Design, build, and maintain scalable data pipelines across internal systems, vendor platforms, and the data warehouse
• Improve data quality, observability, and reliability across core workflows
• Optimize data workflows for efficiency and long-term operational health
• Support both batch and event-driven or CDC-based pipeline patterns
• Own schema design and warehouse modeling strategy, including dimensional and normalized approaches where appropriate
• Help define and implement data governance best practices, including RBAC
• Ensure shared definitions, documentation, and trust in core business data
• Serve as a thought partner to Engineering, Product, Analytics, and business teams
• Translate technical complexity into clear recommendations and tradeoffs
• Raise the bar for data engineering practices across the organization
• Help the company make better decisions through strong, accessible data foundations
• Identify opportunities to improve workflows through automation, tooling, and thoughtful use of AI
• Experiment pragmatically with new technologies and scale what works
• Build systems and guardrails that enable teams to move faster without sacrificing quality

• Design and maintain scalable HR data architecture in Snowflake, including databases, schemas, data models and semantic views.
• Build and optimize ETL/ELT pipelines using Matillion and Snowflake to support reporting, analytics and operational needs.
• Define and enforce data governance, data quality, consistency, lineage, naming standards and compliance with regulatory requirements for HR data.
• Develop and maintain data controls to ensure the integrity and reliability of data across systems and workflows.
• Implement and manage security policies for user views and semantic layers, including role-based access and data protection.
• Manage SQL Server environments used for metadata management, including performance tuning and reliability.
• Establish DevOps practices (version control, deployment automation, environment promotion) for schemas, pipelines and data models.
• Partner with Product and Delivery, BU Consultants and BI development teams to translate requirements into scalable, governed data solutions.
• Provide consultation and guidance on data architecture, integration and analytics capabilities.
• Create and maintain comprehensive documentation for data architecture designs, processes, governance policies, and integrations.
• Support AI-ready and agentic use cases by organizing trusted semantics, metadata and reusable data products.

Data Engineer jobs in Connecticut

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Director, Data Engineering – Business Data

Senior Data Engineer

AI Engineer, AI Experienced Associate

Senior Data Engineer

Senior Software Engineer, Data

Senior Data Engineer

Data Engineer

Data Engineer

Senior Software Engineer, ERP, Data & Domain

Healthcare Claims, Data Engineer

Director, Data Architect

Engineering Development Program – Data Engineering

Director, Scientific Data Platforms Lead

IAM IGA Data Engineer, Assistant Vice President

Data Engineer II

Staff Data Engineer

Lead Director – Provider Data Engineering, Transformation

Director of Engineering – Data Platform

Staff Data Engineer

Manager, Data Architect