Top Remote Senior Level Data Engineering Jobs in Boston, MA

The AV Safety Analytics Engineer will develop data analytics infrastructure for automated vehicle safety, utilizing cloud processing and statistical methods. Responsibilities include creating data visualizations, monitoring metrics, and ensuring data integrity across systems.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead end-to-end data science initiatives: design, deploy, and monitor production ML models for credit risk, pricing, collections, and fraud. Partner cross-functionally to integrate models, set development standards, mentor team members, and maintain reliable, scalable machine learning pipelines and monitoring systems.

The Cloud Data Architect will design and implement data architecture solutions within a SaaS environment, ensuring data security and efficiency while leading technical standards and collaborative teams.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

The Senior Data Engineer handles ChowNow's data platform, collaborating with teams to enhance data availability and insights, supporting internal and customer-facing products.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

Lead design and build of a cloud-based data platform for simulation outputs: architect AWS data warehouse and ingestion, transform high-volume telemetry into trusted datasets, establish schemas/data contracts, enable replay/comparison, support analytics/AI, and hire and mentor a data engineering team.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.