Top Pharmaceutical Data Engineering Jobs

The Principal Data Architect leads technical and business discussions on architecture direction, participates in enterprise strategic development, and manages architecture governance while aligning architectural requirements with IT strategy and business goals.

Assist in developing and maintaining data processing pipelines, collaborating with teams to define requirements, and enhancing infrastructure for data sets.

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.

The Data Engineer II will design data models, build ETL pipelines, collaborate with teams, and ensure data flows are efficient and well-monitored. A strong understanding of SQL, Python, and cloud technology is essential.

Manage data loading processes, ensure data quality, design ETL pipelines, build Power BI reports, and maintain data models while collaborating with business teams.

As a Principal Statistical Programmer, you will lead the design and implementation of statistical programming solutions for clinical trials, ensuring compliance with regulatory standards.

The Junior Data Engineer will build, maintain, and monitor data pipelines for laboratory and R&D functions, ensuring data quality and governance while collaborating with various teams.

The Director of Scientific Computing Operations leads strategies for scientific computing platforms, driving innovation, lifecycle management, operational excellence, and stakeholder engagement in advanced analytics and AI capabilities.

Design, develop, and maintain data solutions to ensure data availability and quality for analytics. Build data pipelines, optimize database designs, and perform data integration and transformation.

The Associate Director is responsible for implementing automation and AI workflows in biometrics, ensuring regulatory compliance, continuous improvement of standards, and collaboration across data management and analysis teams.