Senior Data Engineer

In this role, you will design and deliver robust data pipelines to transform harmonised biomedical data into AI-ready assets for large-scale model training. You will work within the AI Enablement team to enable multimodal data provisioning and model deployment, partnering with IT to ensure the right infrastructure and tooling. You will shape data governance, lineage and benchmarking to support trustworthy AI in biomedical research. This is a chance to contribute to cutting-edge biomedical AI that informs disease biology and targets discovery.

• hybrid work arrangement
• office presence ~3 days a week
• recognition as Top Employer in the UK
• strong HR policies and people practices

• Transform harmonised datasets into AI-ready assets for pre-training and fine-tuning
• Build and maintain entity linking pipelines connecting patients and biomedical entities across modalities
• Develop cross-modal integration pipelines for multimodal training, fine-tuning and inference
• Ensure pipelines comply with data access permissions, consent conditions and usage restrictions
• Maintain data lineage and provenance across datasets
• Create biomedical benchmark datasets with versioning and documentation
• Write clean, well-tested, well-documented code meeting engineering standards
• Contribute to code reviews within the data engineering team
• Stay current with advances in data engineering tooling relevant to biomedical AI

• PhD in a relevant quantitative field
• Strong hands-on experience in data engineering for machine learning
• Experience with at least one biomedical data modality in a data engineering context
• Practical experience with entity linking or record linkage in biomedical/clinical context
• Strong understanding of biomedical data characteristics (variant formats, expression matrices, SNOMED, ICD-10)
• Proficiency with modern data engineering tools
• Familiarity with data governance frameworks for biomedical/clinical data
• Familiarity with Trusted Research Environments or controlled-access biomedical data environments
• Experience with biomedical ontology systems and identifier mapping across modalities
• Contributions to open-source data engineering or bioinformatics tooling

• modern data engineering tools
• entity linking / record linkage
• biomedical data formats (variant data, expression matrices)
• SNOMED, ICD-10