Top Remote Senior Level Data Engineering Jobs in Boston, MA

As a Data Solutions Architect, you will collaborate with clients to define business requirements, showcase AcuityMD's data solutions, and drive commercial effectiveness in MedTech sales through data expertise and presentations.

The Sr. Analytics Engineer at Philo is responsible for designing data models, governing business metrics, collaborating with stakeholders, and ensuring data quality and documentation for analytics purposes.

As a Snowflake Data Architect, you will provide ETL support and specialize in Snowflake management, ensuring performance, governance, and optimization of data infrastructures.

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.

Design, build, and optimize data architecture and pipelines, ensuring data quality and integrity while supporting advanced analytics and reporting efforts.

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.

The Senior Ad Ops Engineer develops and manages data products for marketing activation, focusing on data pipelines, quality validation, and integration with marketing platforms.

The Senior Data Engineer will build and maintain data pipelines, optimize data processing, and ensure data privacy and quality within the healthcare tech space.

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 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.