Top Data Engineer Jobs in Boston, MA

Design and implement large-scale analytics data structures and ingestion pipelines (real-time and batch). Build ETL/ELT processes, participate in technical decisions, review code, and document architecture and solutions for analytics users.

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.

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.

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.

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.

As a Data Engineer II, you will build, scale, and optimize data platforms, focusing on ETL/ELT pipelines, and collaborate with data scientists and AI engineers to support data-driven applications and insights.

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 II at Magnite, you will build and optimize data pipelines with Apache Spark and Python, collaborate on data architecture, ensure operational performance, and work on infrastructure provisioning using Terraform and AWS.

As a Data Engineer at Edmunds, you will architect and maintain data platforms for analytics and AI/ML, ensuring scalable, reliable data processing and supporting cross-functional collaboration.

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

As a Lead Data Engineer, you'll design and maintain data systems and pipelines using Snowflake, ensuring data quality and governance for AI applications.

The Senior Data Engineer will design and optimize large-scale batch and streaming data pipelines using Scala and Spark, oversee the data engineering lifecycle, and engage in technical discussions to improve system efficiency.

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

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

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.

The Principal Data Engineer will lead the design and development of scalable data platforms, optimize data pipelines, and collaborate with multiple teams to enhance data solutions.

Support and monitor ETL processes, data lake and reporting systems; troubleshoot and resolve production failures; create reports and processes as needed; communicate with business partners; participate in scheduled on-call rotations and provide status updates to managers.

As a Lead Data Engineer, you will collaborate with Agile teams, develop technical solutions, and enhance cloud-based data warehousing to empower financial services for customers.

As the first in-house Data Engineer, you will own the data infrastructure, build and maintain data pipelines, and collaborate with teams to ensure quality data access and insights.

Lead architecture and implementation of scalable data pipelines, integrations, and cloud data infrastructure. Own IaC (Terraform), workflow orchestration (near-real-time and batch), third-party API and AI/LLM integrations, data export pipelines, and internal tooling. Mentor engineers, drive technical strategy and cross-team priorities, and communicate tradeoffs to technical and non-technical stakeholders. Must work EST/CST hours and be authorized to work in the US.

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.