Top Data Engineer Jobs in Boston, MA

The Data Engineer will architect and expand data products for Netflix's Ads business, developing data pipelines, collaborating with analysts, and ensuring data quality.

The Data Engineer will manage data ingestion in Salesforce, standardize lead data, ensure data quality, and optimize integration workflows.

The Analytics Engineer will enhance the People Data Warehouse, model data, partner with stakeholders, and ensure data integrity for decision-making.

As a Data Engineer, you will design and implement data platform capabilities, support compliance, and ensure secure data consumption while mentoring clients and improving data pipelines.

The Senior Data Engineer will develop and maintain data pipelines, collaborate with Analysts, and ensure high code and data quality on the Hungryroot Analytics model.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

As a Data Engineer at Monte Carlo, you will build and maintain data pipelines, collaborate with data science teams, and enhance pipeline reliability using the company's own product.

The Growth Data Engineer will manage data infrastructure, build ETL pipelines, ensure data governance, and work cross-functionally to support growth and marketing efforts.

The BI Data Engineer will build data pipelines, develop data models, conduct analyses, and drive BI tool usage across teams.

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

The Data Engineer will design and automate data pipelines, ensure data reliability, maintain reference datasets, and implement ML workflows within healthcare operations.

Design and optimize data pipelines, work with structured/unstructured data, ensure data quality for analytics, and collaborate with data scientists.

Design and implement scalable data systems, define core schemas, build data pipelines, and collaborate with data teams.

The Data Engineer will design and maintain data pipelines, develop data models, ensure data quality, and collaborate with various stakeholders for data solutions.

As a Data Engineer, you'll manage data access, support development and analytics teams, implement automated processes, engineer data pipelines, and ensure data accuracy.

Lead the implementation of AML detection pipelines using Palantir Foundry. Train team members in technical skills and oversee data architecture and maintenance.

You will design and build data-driven Streamlit apps, automate analytics pipelines, and monitor application performance while collaborating with platform engineers.

Design, build, and maintain scalable data infrastructure in the cloud using AWS services and Infrastructure as Code to ensure data reliability and performance.

The Sr. Data Engineer will build and optimize data pipelines, support data strategies, and leverage AI tools, with a focus on software engineering best practices.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

The Senior Data Analytics Engineer designs and implements data models and analytics solutions, oversees data pipelines, and collaborates with teams to drive insights.

In this role, you will design and maintain ETL processes, collaborate with teams for data insights, and utilize various programming tools to enhance operations.

As a Staff Data Engineer, you will enhance and modernize data platform infrastructure, manage data processing platforms, and mentor junior engineers.

The Senior Data Engineer will focus on ingesting and curating satellite imagery and geospatial data, building data pipelines, and mentoring junior engineers, while ensuring performance and scalability.

Lead the design and implementation of a modern data architecture, manage ETL pipelines, ensure data quality, and collaborate with cross-functional teams.