Top Data Engineer Jobs in Hartford, CT

Lead the development of AI data pipelines, improve data capabilities, integrate AI solutions, mentor team members, and ensure operational efficiency.

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

As a Data Engineer, you'll build data solutions, support analytics, and ensure data quality while collaborating across teams to optimize data management.

Design, build, and operationalize data and ML pipelines on Databricks. Implement CI/CD and infrastructure-as-code, ensure data quality/governance, troubleshoot incidents, and collaborate cross-functionally to enable reproducible ML lifecycle and deployments.

The Data Engineer will build and operationalize data solutions, design complex data systems, collaborate across teams, and ensure high-quality data management.

The Data Engineer will build and operationalize data solutions, analyze data sources, ensure data governance and quality, and support analytics across teams.

The Data Engineer will design and maintain data models on Snowflake, enforce data standards, manage security, optimize SQL, implement CI/CD, and mentor junior staff.

Design, build, and validate pipelines to ingest, standardize, and publish real-world healthcare datasets (claims, EMR, registry). Perform SQL, Python, and SAS transformations, OMOP conversions, QA, and vendor communications to deliver high-quality datasets for analytics and research.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Sr GenAI Data Engineer will design and implement AI-driven data solutions, improving data capabilities and integrating with enterprise systems while mentoring junior team members.

The Data Engineer will build and optimize data pipelines, manage data flow, and collaborate with Analytics and Business teams to support data-driven insights and systems.

Lead the development of AI solutions and data engineering strategies. Implement AI data pipelines, collaborate with teams, and ensure the reliability of data systems.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

As a Data Engineer II (Tech Lead), you will design and build complex data solutions, optimize data transformation processes, and collaborate with teams to enhance analytical capabilities across the organization.

The Data Engineer will build and maintain data infrastructure, design data pipelines, and develop reusable frameworks, leveraging technologies like Azure Databricks and PySpark for data processing and transformation.

The Data Engineer will enhance the Enterprise Data Warehouse, modernizing ETL processes, optimizing data transformations, ensuring data quality, and providing production support while collaborating with cross-functional teams.

Design, build, and operate Spark-based ETL pipelines on AWS. Collaborate with stakeholders to deliver reliable data products, ensure data quality and governance, optimize performance, and maintain operational excellence of the data platform.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

Design, build, and optimize distributed query solutions using Starburst/Trino. Enable secure, governed data access across cloud and on-premises sources, implement data federation and query optimization, support IAM and governance in a federal environment, develop backend services and CI/CD, and troubleshoot performance in cloud-native systems.

Design, build, monitor, and optimize large-scale ETL/ELT data pipelines and data architecture. Integrate data sources, support analysts and data scientists, automate processes, ensure reliable data delivery, and write maintainable code.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.