Data Engineer Jobs in Cambridge, MA

Develop, deploy, and operate production-grade Nextflow pipelines and cloud-based omics data platforms. Integrate and harmonize complex biological and clinical datasets (single-cell, bulk transcriptomics, ATAC-seq, proteomics, genetics) for ML model training and inference. Implement DevOps and CI/CD practices, manage pipeline lifecycle, collaborate with scientists and external partners, and deliver reusable, scalable data products to support AI-driven discovery.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

The Data Engineer will design and build data solutions, develop ELT jobs, ensure data quality, and collaborate with technical teams to align data strategies with business goals.

Design, develop, and validate advanced ML and quantitative models for pricing and market-making. Analyze large market and sports datasets, build scalable data pipelines and real-time algorithmic engines, deploy and monitor models in production, establish best practices for backtesting and evaluation, and mentor teammates to raise technical standards.

Lead Data Engineer will design, build, test, and support cloud-based data solutions and streaming systems. Collaborate with Agile teams and product managers, mentor engineers, implement big data tooling (Spark, Kafka, EMR), and optimize data warehousing (Redshift, Snowflake) using Java/Scala/Python and SQL. Ensure code quality with unit tests and reviews.

Design, build, and maintain scalable cloud-based data pipelines and models (AWS, Snowflake). Implement ETL/ELT, data quality checks, automated tests, and monitoring. Collaborate with product owners, data scientists, and stakeholders to translate requirements, perform data profiling and troubleshooting, document data flows, and drive continuous improvements.

Lead technical strategy and implementation of V-BAT fleet data analysis pipelines and tooling. Transform raw flight, simulation, and production data into metrics, dashboards, and reports; perform fleet-wide studies, anomaly investigations, and root-cause analysis; partner with cross-functional teams and mentor engineers on analysis best practices.

Develop and maintain data-protection features in CrowdStrike Falcon sensor on Windows, working across kernel and user mode. Implement filesystem minifilter drivers, AI-aware detection/protection logic, debug kernel issues, own features end-to-end, and collaborate with cross-functional teams to ship and support endpoint data security capabilities.

Embed with enterprise clients to discover, build, and deploy AI agent workflows against messy, unstructured data. Lead technical onboarding, construct connectors and pipelines, run production deployments, serve as primary technical contact, feed product insights back to engineering, and create repeatable implementation playbooks.

The Data Engineer will develop data pipelines, support automation, and collaborate within an Agile team to manage complex data sets, ensuring performance and reliability in data processing.

Build and maintain R&D data infrastructure for experimental, manufacturing, and QC data. Implement DAQ integrations, databases, validation checks, analysis pipelines, visualizations/dashboards, and perform statistical/regression analyses to support cross-functional technical teams.

The Data Engineer designs and builds data pipelines for analytics, ensuring data quality, governance, and integration across systems, while collaborating with teams for effective delivery.

Lead architecture and design of the Beacon Datastore: define scalable data models, build event-driven pipelines, implement features, draft RFCs, coach engineers, and align platform standards to support analytics and clinical workflows.

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.

As a Software Engineer II on the Data Automation team, you will design and maintain the analytics infrastructure, collaborating with teams to ensure high system performance and reliability.

Design, build, and maintain large-scale ETL/ELT data pipelines and cloud data architectures (AWS/Azure). Optimize Spark/Databricks/Synapse jobs, orchestrate workflows with Airflow, manage SQL/NoSQL databases, implement governance/security, create dashboards, integrate APIs, support ML model pipelines, and deploy using Docker/DevOps practices while monitoring pipeline health.

Lead operational design and engineering for the data platform: own Snowflake and dbt administration, automate platform operations and CI/CD, monitor platform health and observability, enforce governance and access, optimize performance and costs, and develop AI/agent integrations to enable governed data access for business users.

The Data Engineer will develop and optimize data pipelines for LLMs, ensuring high-quality healthcare datasets while collaborating with data scientists on model requirements.

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

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.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Lead end-to-end machine learning projects to improve customer engagement and retention. Build, test, and deploy models for user forecasting, personalization, and Casino engagement. Partner cross-functionally to scale solutions, mentor junior data scientists, and communicate model impact to influence product and marketing strategy.