Top Data Engineer Jobs in Boston, MA

Operate and own real-time, petabyte-scale streaming pipelines (Pub/Sub/Kafka, Dataflow/Beam), integrate LLMs/Vertex AI enrichment, build monitoring/alerting, respond to incidents, ensure data integrity, and collaborate with Product and Analysts to improve observability and reliability.

Lead graph data engineering to design, implement, and scale Neo4j-based graph platforms. Build graph models, ingestion pipelines (batch and streaming), integrate graphs with analytics/ML, establish governance, and enable graph-driven business use cases like fraud detection and Customer 360.

Lead design, build, and operate real-time, Flink-based streaming data platforms. Develop low-latency, stateful pipelines, enforce event schemas/contracts, ensure fault tolerance and observability, mentor engineers, and partner with architecture and compliance teams to deliver resilient streaming solutions for banking use cases.

Lead architecture and implementation of a large-scale analytics stack: design foundational pipelines, establish modeling/orchestration standards, integrate AI-assisted engineering tools, translate business questions into version-controlled data models, partner with stakeholders to define metrics and data contracts, migrate logic into maintainable pipelines, and optimize cloud warehouse performance for scale.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

The Data Engineer III will lead the development and maintenance of data infrastructure and tools, ensuring data integrity while driving strategic data initiatives.

Design, build, and maintain an internal data platform and pipelines. Ensure secure, governed, resilient data access for engineering and BI teams. Partner with architects, implement automations, support platform consumption, mentor users, and drive continuous improvement and compliance.

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.

Lead design and delivery of Databricks Lakehouse pipelines (Bronze/Silver/Gold) as a hands-on engineer. Build production SQL/Python/Spark pipelines, own Gold schema, implement data quality and alerts, onboard external data, manage contractors, and partner with decision intelligence and software teams to supply features for AI models and decisioning.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.

The role involves designing and optimizing data pipelines in Snowflake, developing ETL workflows, collaborating on data integration, ensuring data security, and performance monitoring.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

Forward-deployed senior data engineer who deploys, hardens, integrates, and operates a data platform (lakehouse, streaming, governance) in DoD environments. Build pipelines across classification boundaries, produce accreditation evidence (STIG/cATO/FIPS), run day-2 operations, train mission teams, and mentor junior FDEs while feeding field feedback into product improvements.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

The Data Engineer I at Storable supports the design and maintenance of data pipelines, works with ETL processes, optimizes workflows, and collaborates with various teams to enhance data accessibility and reliability.

The Looker Data Engineer will build and optimize data models, develop reporting solutions, and support data-driven decisions using Looker and other technologies.

The Forward Deployed Data Engineer at ZoomInfo designs and delivers custom intelligence applications for strategic accounts, managing engagements end-to-end and collaborating with various teams to optimize data solutions.

Design, build, and maintain scalable batch and near-real-time data pipelines and data products using Databricks and Spark. Integrate internal/external sources, implement data models, ensure data quality, support BI (Sisense), CI/CD, and collaborate with analysts, scientists, and stakeholders to enable analytics and decision-making.

Design, build, and maintain scalable ELT data pipelines and models to power reporting, analytics, and operational workflows. Troubleshoot data quality and performance, participate in incident response, support CI/CD deployments, collaborate with cross-functional teams, and contribute to data platform modernization and engineering best practices.

Support building and maintaining ETL/ELT data pipelines and cloud data workflows. Work with senior engineers and cross-functional teams to implement, test, deploy, and document data processes. Continuously learn cloud technologies, SQL, and Python/PySpark, follow coding best practices, and contribute to process improvements in an Agile environment.

Build and maintain scalable data pipelines and integrations using Databricks and Azure. Transform and model large structured and unstructured datasets to support reporting, analytics, and operational needs. Implement data quality, monitoring, and governance; troubleshoot pipeline performance; collaborate with stakeholders and mentor junior engineers.