Top Pharmaceutical Data Engineering Jobs

Transform Electronic Health Records (EHR) data into structured assets, build scalable data pipelines, and apply Generative AI techniques for analytics within a healthcare-focused team.

The Data Analytics Engineer will manage data integration, create dashboards, analyze healthcare data, and support decision-making in a collaborative environment.

As an Experienced Compound Logistics Scientist, you will manage research compounds' inventory and sample workflows while innovating logistics processes and improving automated systems.

The Statistical Genetics Platform Engineer will develop scalable computational pipelines and tools for statistical genetics analyses, collaborating with researchers to enhance data-driven decision-making in therapeutic target evaluation.

As a Senior Clinical Data Science Programmer, you will develop and implement programming solutions, collaborate with scientists, generate datasets, and ensure data accuracy in clinical trials.

The Clinical Data Validation Engineer will lead the development and implementation of data science solutions for clinical trials, ensuring data integrity and overseeing programming activities.

The principal statistical programmer provides programming support for clinical studies, ensuring data processing, validation, and project coordination according to statistical analysis plans.

The role involves developing clinical modeling prototypes and analytics platforms, optimizing trial processes, and creating user-friendly operational tools. Collaboration with teams to enhance data insights and compliance with governance standards is key.

The Data Analytics and Integration Specialist is responsible for developing ETL processes, managing AWS data pipelines, and ensuring data security and compliance. They will develop data models, optimize data handling, and document architectures.

The Director of Data Engineering will lead the engineering team in building a scalable data platform, ensuring data quality and compliance, while collaborating with various stakeholders to enhance analytics capabilities.

Design and develop innovative deep learning methods for biomolecular design, collaborating with biology teams, prototyping new algorithms, and presenting results.