Top Data Engineer Jobs in Boston, MA

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Lead design and implementation of data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Design, build, and optimize BigQuery-based data solutions and data models. Manage data storage, partitioning, clustering, ETL, and data quality. Collaborate with architects, data scientists, and engineers to deliver scalable, secure cloud data infrastructure and documentation; senior hires provide technical leadership, code review, and process improvement.

As a Data Engineer, you'll transform raw data into refined offerings, collaborate with stakeholders, build central logic layers, and leverage AI tools for efficient data workflows.

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.

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 Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Lead and mentor a data engineering team to design, build, test, and support cloud-based, real-time data platforms and distributed microservices using modern big data, streaming, and data warehousing technologies to deliver scalable customer and enterprise experiences.

Lead design, develop, test, deploy and support cloud-based data engineering solutions. Work across Agile teams on distributed, real-time and batch data platforms, mentor engineers, and optimize code and data pipelines using big data, streaming, and cloud data warehousing technologies.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

Lead Data Engineer responsible for designing data models, implementing data solutions, managing data pipelines, and collaborating with teams to drive technical initiatives.

Build scalable cloud data infrastructure and pipelines to transform transactional and financial data into reporting-ready datasets. Ensure accuracy, traceability, governance, and observability; partner with cross-functional teams, mentor engineers, and leverage AI-assisted tools to improve engineering productivity and enable AI-powered applications.

The role involves engineering modern data platforms, focusing on data ingestion, transformation, and storage while utilizing Azure services and MS Fabric, supporting an investment management firm.

Build and maintain reliable data pipelines, Airflow DAGs, and Snowflake-based Data Vault/warehouse models. Implement CI/CD, automated testing, observability, and production support while partnering with stakeholders and developing insurance domain expertise.

The role involves building and improving WHOOP's data platform infrastructure, ensuring reliability and efficiency, and driving best practices across engineering and data workflows.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

Design, build, and maintain high-throughput data processing services, focusing on streaming and batch data systems to enhance player experiences.

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Build and maintain scalable, governed data pipelines from ingestion through transformation and integration. Implement schema validation, data quality checks, job monitoring, and production-grade APIs. Work with Python, SQL, Airflow, dbt, AWS (EMR, Athena, S3), Iceberg/Parquet, and contribute to CI/CD, observability, and on-call support while collaborating with analytics and product teams.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.

Design, build, and maintain enterprise ETL/ELT pipelines and data management workflows for market, reference, and financial data in the Markit EDM platform. Implement ingestion, validation, reconciliation, enrichment, monitoring, and distribution processes; support reporting and downstream integrations. Troubleshoot production data issues, collaborate with stakeholders in agile squads, and mentor junior engineers to promote best practices.

Designs and implements cloud-based single and multi-tenant data solutions, PoCs, real-time pipelines and ETL/ELT processes using Snowflake, AWS, Python and Informatica. Builds and tunes databases and stored procedures, develops APIs with Spring Boot/Java/Python, applies CI/CD, leads architecture and QA, manages project lifecycle, advises on risk and technical strategy, and mentors junior engineers.