We are working with a global biopharmaceutical organisation dedicated to transforming patient outcomes through pioneering research and development. With a strong focus on serious and complex conditions, this company combines advanced science, innovative technologies, and a patient-first approach to deliver new therapeutic solutions. This is an opportunity to join a collaborative, science-led team making a tangible impact on global healthcare.

This role will offer you:

• The opportunity to work on diverse, high-impact data engineering projects across multiple research and development areas, including Clinical Trials, Omics, Real World Data, and more.
• Collaboration with international teams of researchers, data scientists, and stakeholders in a cross-functional setting.
• Exposure to cutting-edge cloud technologies, modern data architecture, and the latest in healthcare data standards.
• A meaningful role where your work directly supports the development of life-changing medicines.

Responsibilities:

• Design, develop, and maintain data pipelines for diverse research datasets using cloud-based technologies.
• Create and optimise ETL/ELT processes for structured and unstructured data.
• Build and manage data repositories and warehousing solutions.
• Develop and implement data quality frameworks, validation processes, and KPIs.
• Ensure data traceability and regulatory compliance through versioning and lineage tracking.
• Collaborate with internal teams to understand data requirements and deliver scalable solutions.
• Maintain compliance with data privacy regulations such as GDPR and HIPAA.
• Document architectures, workflows, and data processes while applying modern DevOps best practices.

You will bring:

• Strong proficiency in programming languages such as Python, R, and SQL, with experience in cloud-based services for data engineering.
• Solid understanding of relational databases, data modeling, and unstructured database technologies (e.g. NoSQL, Graph).
• Familiarity with containerisation (e.g. Docker, Kubernetes/EKS) and Agile working environments.
• Exposure to healthcare data standards (CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM) and relevant regulatory requirements.
• A Bachelor’s degree in Computer Science, Statistics, Mathematics, Life Sciences, or related fields (Master’s preferred).
• 3–5 years’ experience in data engineering, including experience working with healthcare, research, or clinical data.