Top Data Engineer Jobs in Boston, MA

Design and maintain data engineering pipelines for Yahoo's Consumer Monetization Platform, leveraging Machine Learning, analytics, and large data infrastructures.

As a Senior Data Engineer, you will design and implement scalable data solutions, collaborate with teams on AI/ML products, and lead complex data projects.

As a Data Engineer, you will design and implement data pipelines, optimize workflows, and support analytics using AWS and GCP, collaborating with teams to enable data-driven decision-making.

The Senior Analytics Engineer will design and maintain data models, develop user-facing data products, optimize BI systems, and troubleshoot data pipelines while ensuring data quality and security standards.

As a Senior Data Engineer, you will develop E2E data pipelines, manage data ingestion, integrate data layers, and improve data architecture while collaborating with cross-functional teams.

Looking for Sr. Azure Data Engineers with 8+ years of experience. Responsibilities include building data pipelines and integrating data from various sources.

Responsible for designing and building distributed data systems, developing robust data pipelines, and architecting data platforms to support large-scale data processing.

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

As a Data Engineer, you will work with clients to understand data distribution needs, build extracts and optimize scripts, while fostering a collaborative team culture.

The Associate Data Engineer will assist in developing and optimizing data pipelines, collaborating with teams to ensure data integration and transformation using Snowflake.

Design and build data pipelines for insights, collaborate with teams, and optimize data solutions using Snowflake and AWS.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

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

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.

As a Senior Data Engineer, you will lead data infrastructure projects, manage ETL pipelines, collaborate with analysts, and improve data models and processes.

As a Senior Data Platform Engineer, you will develop tools for data quality checks, enhance data lineage framework, and improve data infrastructure performance.

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.

The Data Engineer II will design and optimize scalable data pipelines for machine learning and analytics, collaborating on data-driven solutions with various teams.

The Data Engineer I will build robust data models, maintain data infrastructure, ensure data quality, and collaborate with analysts and scientists for business insights.

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

The Epic Cogito Data Engineer will gather reporting requirements, design and develop reports, and provide post-implementation support in healthcare IT.

Design and maintain data pipelines, manage Hightouch syncs, optimize SQL queries, troubleshoot issues, and collaborate with stakeholders. Requires 5+ years in data engineering.

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.