Top Data Engineer Jobs in Boston, MA

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

The Data Engineer II role involves optimizing data architecture, developing data pipelines, and supporting analytics initiatives for cross-functional teams.

The Data Engineer II will design data models, build ETL pipelines, collaborate with teams, and ensure data flows are efficient and well-monitored. A strong understanding of SQL, Python, and cloud technology is essential.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

Build and own end-to-end sales data pipelines and curated marts in Snowflake/dbt; implement monitoring, tests, and governance; run reverse-ETL to operational systems; partner with Sales, Ops, Finance, and People to deliver production-ready analytics products.

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.

The Data Analytics Engineer will develop data models, perform data wrangling, and create dashboards to drive insights for business decisions at Bose Corporation.

This co-op position involves developing data products, design and testing of data pipelines, and delivering insights from complex datasets for business decisions.

This co-op position involves developing data products and solving complex data problems using cloud technologies, SQL, and programming languages while gaining mentorship and business exposure.

The Senior Data Engineer II will design and maintain scalable data pipelines, collaborate with teams on machine learning workflows, and ensure data accessibility across systems.

Transform Electronic Health Records (EHR) data into structured assets, build scalable data pipelines, and apply Generative AI techniques for analytics within a healthcare-focused team.

The Senior Technical Consultant will design and build data integration solutions, ensuring data accessibility, governance, and integrity while collaborating with teams to enhance data pipeline efficiency.

As a Senior Data Engineer, you will enhance data products, build automated data pipelines, and improve data platform capabilities, collaborating with various teams to drive initiatives.

The Data Engineer will design and optimize ETL jobs using PySpark, build data pipelines, and collaborate on enterprise data systems.

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 Senior Data Engineer will architect, build, and maintain scalable data pipelines and infrastructure, mentor junior engineers, and collaborate on data solutions for Openly's insurance platform.

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.

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.

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.

The Data Engineer will build and maintain data pipelines, ensuring high-quality and scalable data systems while working on analytics and machine learning accessibility.

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.