Data Engineer Jobs in Cambridge, MA

Partner with stakeholders to define metrics and deliver dashboards and insights. Build and optimize data models in Amazon Redshift, design and maintain scalable ETL pipelines using Python and Apache Airflow, monitor data quality and pipeline performance, and participate in code reviews and engineering best practices to support analytics and reporting needs.

Lead development of large-scale data analysis and validation workflows for autonomous driving ML. Design metrics, build datasets, run statistical error and regression analyses, collaborate with ML and software teams, and maintain AWS/Kubernetes orchestration for large-scale evaluation.

Partner with portfolio-company leaders to translate business problems into quantitative frameworks, build predictive models and analyses, and drive strategy and execution. Lead AI assessments, identify growth opportunities, present recommendations to executives, and implement measurable data-driven initiatives across finance, pricing, operations, and marketing.

The Senior Data Engineer will build data pipelines and infrastructure, modernize legacy systems, and ensure data reliability for analytics at ABCorp.

As a Software Engineer in the Data Platform team, you will implement data governance frameworks, manage access controls, improve data quality, and support audit readiness.

Hands-on Senior Data Engineer to maintain and optimize an Oracle-centric enterprise data warehouse, manage cloud-to-Oracle integrations, evolve ETL/ELT pipelines, and help build a hybrid lakehouse (Apache Iceberg, OCI Object Storage, Parquet). Requires performance tuning, Linux administration, Java debugging, and close collaboration with senior client stakeholders. Contractor role with possible conversion to full-time.

Join an elite engineering team to develop massive data processing systems using Core Java and AWS, focusing on Big Data and performance optimization.

Design and implement scalable LLM- and RAG-based systems integrating knowledge graphs and multi-omics data, build agentic orchestration and conversational AI, collaborate with data engineering and experimental scientists, and deploy pipelines that synthesize biological information to support therapeutic discovery.

Lead design, implementation, and optimization of data pipelines, models, reports and Power BI/SSMS dashboards for public safety clients. Configure analytics databases, train agency users, produce instructional materials, mentor junior engineers, and serve as technical SME and escalation point for multi-agency analytics implementations.

The Senior Data Engineer will design, implement, and maintain data pipelines, improve data quality, and support investment data management, collaborating within a team to enhance decision-making and reporting capabilities.

Build and maintain Snowflake/dbt data pipelines and models for a Customer Data Platform, integrate complex source systems, own architecture decisions and ADRs, ensure data quality via automated tests, collaborate with cross-functional stakeholders, and mentor junior engineers.

The Staff Engineer will lead technical direction on data infrastructure, focusing on ingestion frameworks, storage architecture, and orchestration to support scientific workflows. Responsibilities include mentoring, ensuring reliability, and collaborating with cross-functional teams to establish coding standards and data integrity.

Design, build, and scale data-driven solutions and high-volume ETL/ELT pipelines for equity research. Develop cloud-based (AWS) data architectures, ensure data modeling, governance, performance tuning, and collaborate with data scientists and business partners in Agile environments.

Senior technical leader embedded in a Scrum team to design, build, and maintain scalable batch and real-time data pipelines and services; lead data modeling and warehousing; enforce data engineering best practices, quality frameworks, SLAs/SLOs, and observability; translate product and analytics needs into durable data platforms; mentor engineers and influence cross-team technical direction.

Design, build, and optimize the company lakehouse environment and ETL/ELT pipelines (Databricks/Azure/Fabric). Develop semantic models, governed metrics, data quality controls, monitoring, and CI/CD practices. Partner with business, security, and analytics teams to steward master data, implement governance and access controls, and enable reliable datasets for reporting and AI use cases.

Build and maintain full-stack internal applications: backend services/APIs, frontend UIs (React), and workflow automation. Own features end-to-end, drive architecture discussions, ensure testability, maintainability, and quality through code reviews.

Design, develop, and maintain scalable data platform components and distributed system software. Build batch and streaming data pipelines, implement data-science algorithms, optimize data delivery, automate processes, and contribute in an Agile environment. Perform unit testing, code reviews, and generate technical documentation while mentoring junior engineers.

Design, develop, and maintain scalable data platforms and batch/streaming pipelines. Implement data scientist algorithms, drive engineering best practices, mentor junior engineers, improve processes and infrastructure, and contribute to distributed system software and CI/CD in an Agile environment.

Design, build, and maintain scalable, secure data pipelines and platforms to acquire, transform, and store large financial datasets. Enable AI/GenAI-ready data foundations for model training, inference, retrieval, and RAG workflows. Collaborate with cross-functional teams, ensure data quality, governance, observability, and compliance, and support production deployments and troubleshooting.

Responsible for finding audio data sources, managing the cloud infrastructure for the ingestion pipeline, and collaborating on dataset roadmaps for AI products.

The Principal Software Engineer will design and build APIs, optimize database architecture, enhance performance, and collaborate on cloud infrastructure for scientific applications.

The role involves developing applications and tools for data visualization in clinical trials, managing projects, and ensuring compliance with data standards. Responsibilities include programming in R, creating dashboards, and integrating data across clinical systems.

Design and implement a scalable cloud-native data and HPC platform for research, contribute features, ensure high quality via testing and tooling, participate in support rotations, and mentor junior engineers.

The Engineer will operationalize scientific tools and methods within the Data Foundry, building deployment pipelines, model serving infrastructure, and ensuring APIs are robust and analytics-ready for both scientists and AI agents.

The Automation Engineer designs, develops, and maintains data pipelines and API integrations for scientific workflows while ensuring compliance with industry standards. The role involves collaboration with scientists and the use of various technologies to optimize data processes.