Top Data Engineer Jobs in Boston, MA

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

The role involves building and maintaining data infrastructure, developing data pipelines, optimizing data models, collaborating with teams to provide actionable insights, and deploying AI-driven solutions.

The Data Engineer will manage, optimize, and expand data infrastructure for a clinical data registry, focusing on building automated data pipelines and supporting healthcare advancements through data insights.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

The Junior Data Engineer will analyze data, build and maintain data pipelines, support CI/CD processes, and assist in IT modernization efforts for a Federal client.

The Staff Data Engineer will build and manage a data lake, optimize data pipelines, collaborate with teams, and support AI projects while ensuring quality data solutions.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

The Data Engineer will build and scale data systems, manage data pipelines, ensure data quality, and collaborate with cross-functional teams to utilize entertainment data effectively.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

The AWS Data Engineer will design, build, and optimize data pipelines on AWS, ensuring performance and data quality for analytics. Responsibilities include developing ETL processes, collaborating with teams, and monitoring data workflows.

This role involves building and maintaining data pipelines, developing data models, and ensuring data discoverability while enabling scalable analytics on blockchain data.

The Data Engineer designs and maintains scalable data infrastructure to support enterprise products, ensuring efficient data ingestion, transformation, and delivery across systems while collaborating with cross-functional teams.

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

Design, build, and maintain scalable, reliable data pipelines and services. Write well-tested Python and SQL code, work with orchestration (Airflow), containers, and cloud infrastructure. Collaborate cross-functionally to deliver data products and improve development processes.

Build and maintain Databricks-based ETL/ELT pipelines, transform and model data, optimize workflows, monitor and troubleshoot pipelines, and collaborate with cross-functional teams.

The Principal Data Engineer will design and implement enterprise data frameworks, mentor teams, and ensure data quality while collaborating with stakeholders.

The Data Engineer I will manage data warehouses, extend data pipelines, write SQL and Python scripts, and support data operations.

The Data Engineer will build ETL pipelines and data infrastructure, ensure data quality, and implement modern data warehousing for analytics improvements, while collaborating with stakeholders across teams.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.