Top Pharmaceutical Data Engineering Jobs in Boston, MA

As a Senior Data Engineer, you'll design scalable data models, build automated ETL pipelines, and mentor junior engineers while collaborating across teams.

The Principal Data Engineer will lead technical consulting efforts, manage data engineering projects, ensure quality control, and mentor team members while focusing on clinical data software and analytics solutions.

The Senior Data Engineer will build and scale data infrastructure, create data models, develop ingestion pipelines, and ensure data quality for drug development at Formation Bio.

The Principal Data Architect II will develop a scalable, cloud-native data platform to enhance AI and ML solutions for biotherapeutics and genetic medicine. Responsibilities include defining data architecture, integrating datasets, and ensuring effective data governance while collaborating with various scientific teams.

Lead the Knowledge Graph & Semantics function at Vertex, defining strategy and building enterprise knowledge graphs to enhance AI and analytics capabilities across the business.

Lead enterprise data platform strategy and architecture focused on Microsoft Fabric. Design, operate, and scale secure global data platforms, own SLAs and operations, enable reliable data pipelines, enforce governance and security, and partner with analytics, AI/ML, cloud, and security teams.

The Manager, Data Science - Oncology will lead data engineering initiatives, optimize workflows, and support data projects, specifically in Oncology R&D. Responsibilities include developing data pipelines, managing a technical team, and collaborating with stakeholders to deliver data solutions.

Lead patient analytics data engineering for LillyDirect, ensuring HIPAA compliance and delivering scalable data products. Collaborate with multi-functional teams on data solutions.

The Data Architect Director will design and govern enterprise data architecture, support commercial analytics, and ensure seamless data integration across the organization.

The role involves developing, validating, and maintaining SDTM and ADaM datasets using R, supporting TLF generation, performing QC checks, and collaborating with various stakeholders in the clinical data environment.