Lead Data Engineer

- Build, optimise and operate ELT/ETL pipelines into our data platform using SQL and Python (PySpark), with a focus on reliability, performance and maintainability. - Develop and maintain core data models (curated layers, dimensional models, shared definitions) that enable consistent KPI reporting and analysis. - Implement and embed data quality controls (freshness, completeness, accuracy, reconciliation checks) and monitoring so issues are detected early and fixed at source where possible. - Partner with analysts and stakeholders to turn business questions into reusable, well-governed data products rather than one-off reporting. - Improve engineering standards: Git workflows, code review, documentation, repeatable deployments, and sensible environment separation. - Support governance by helping define data contracts, ownership, lineage and what does this metric mean? clarity, so teams can use and challenge the numbers confidently. - Contribute to the wider platform roadmap while keeping delivery outcomes front and centre. - Lead by example on engineering quality: set the bar for production-grade delivery (testing, monitoring, documentation, code review, release discipline) and help the team consistently meet it. - Coach and uplift others: mentor junior engineers/analysts, run pairing sessions, provide practical feedback, and help raise SQL/Python capability across the function.