Top Pharmaceutical Data Engineering Jobs in Boston, MA

Build and maintain batch ETL/ELT pipelines and Airflow orchestration using Python, SQL, and AWS. Develop operational datasets for fulfillment, inventory, shipments, and returns. Monitor and optimize pipelines, implement data quality checks and alerting, support production incident response, and collaborate with engineering, BI, and operations teams to improve pipeline scalability, observability, and reliability.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

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 Statistical Programmer leads project teams, ensuring accuracy in SAS programming, regulatory compliance, and effective communication among cross-functional teams.

The Senior Data Engineer will design and implement data pipelines, optimize performance, ensure data quality, and collaborate with teams for analytics and reporting.

The Data Architect will design data infrastructure for AI-native drug discovery, focusing on data models, ontologies, and data platform architecture to support scientific workflows and analytics.

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

The VP of Data will lead the data organization encompassing engineering and analytics, drive strategic insights, improve operational excellence, and integrate AI into workflows while ensuring data governance.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.