Data-Flow Lead
GSK
In this role, you design and govern end-to-end data flows for GSK’s R&D, turning scattered sources into modular, reusable pipelines. You embed compliance and governance into the data fabric, enabling trusted, automation-ready data for faster decision-making. You will work with cross-functional teams to translate business needs into technical data requirements and deliver scalable data-flow products that drive scientific outcomes. A key hook is shaping data flows as products within a large, matrixed organization to support R&D at scale.
Responsibilities- Translate business needs into technical data requirements and processes for seamless data-flow integration across the R&D ecosystem
- Design, develop and maintain modular end-to-end data-flows integrating systems and data sources into trusted reusable assets
- Ensure data-flows are compliant-by-design and orchestrate data and systems per governance principles
- Deliver pre-packaged, curated data-flows with documentation detailing processing steps
- Integrate diverse data-flows (e.g., protocol development, DSUR, clinical trial IHD) into a unified machine-readable format
- Ensure quality controls, documentation, and handover readiness to scale implementation by other teams
- Quantify business impact and value creation from data-flow activities
- Coach and peer-review to uphold industry best practices and data standards
- Degree-level education in Computer Science, Mathematics, Statistics or related subject; BS/MSc/PhD(or equivalent)
- Experience translating business needs into technical data requirements and measurable value from data-flow activities
- Knowledge of metadata ecosystems and agentic solutions
- Hands-on experience with policy engines and Policy as Code
- Experience integrating multiple data sources into unified reusable data-flows with data privacy by design
- Proficiency with Azure and/or GCP and interest in AI/digital tech to boost efficiency
- Strong collaboration in a complex matrix environment
- Problem-solving mindset with a clear rational approach
- Stakeholder management and effective communication
- Data-flow design and orchestration
- Policy as Code and governance automation
- Metadata ecosystems
Reference: WJ-747_31173290