We are seeking a Data Engineer to support the implementation of Health Assessment Outcomes and AI Personalisation Projects. These initiatives are part of a multi-year programme aimed at delivering measurable impact through advanced clinical statistical techniques and innovative AI solutions. The successful candidate will design, build, and maintain robust data pipelines and infrastructure that underpin our data platforms and analytics capabilities

• Review and optimise current data extraction processes, identifying opportunities for performance improvements and reliability.
• Refactor SQL scripts into modular, reusable units to improve maintainability and scalability across projects.
• Evaluate current data pipeline architecture to ensure robustness, efficiency, and alignment with clinical data requirements.
• Implement structured orchestration for previously manual or ad hoc data workflows.
• Introduce versioning practices to track changes and ensure reproducibility.
• Establish testing frameworks to validate data integrity and pipeline performance.
• Define and enforce consistent output schemas to facilitate downstream integration and reuse.
• Develop shared code libraries and maintain comprehensive metadata and documentation to support collaboration and transparency.
• Design and deploy observability tools and practices to monitor, log, and troubleshoot clinical data pipelines effectively.

• Expert-level SQL proficiency and Python fluency.