Lead Data Engineer- £75,000 Does Not Offer Sponsorship Industry: Banking and Financial Services Location : Hybrid- Basingstoke (3 Days a Week) Key Responsibilities Lead the evolution of our data engineering practice, supporting modernisation, automation, and scalability. Design and optimise Databricks architecture, data models, and deployment standards. Re-build and re-platform core components to handle growing data volumes and business demand. Implement better controls around change management, lineage, and deployment (DevOps for data). Introduce new tooling around change deployment and governance in partnership with external consultants. Improve data quality through robust monitoring, testing frameworks, and alerting solutions. Maintain and modernise SQL workloads, including legacy databases and reporting environments. Support upgrades, platform enhancements, and new data tooling selection. Provide best-practice guidance to the wider data function and line-manage up to 3 individuals. Ensure documentation, data dictionaries, lineage, and governance standards are embedded across the team. Essential Skills Strong expertise with SQL, particularly Databricks SQL. Demonstrable experience designing data models (e.g., star schema) and scalable architecture. Knowledge of Azure Modern Data Warehouse tools: Synapse, Databricks, Delta Lake, Unity Catalog. Experience with pipeline orchestration (e.g., Synapse pipelines). Proven background in ITIL change management and incident management. Implementing data quality controls, monitoring, and alerting in production environments. Experience managing data lineage, glossaries, and data dictionaries. Nice to Have Exposure to legacy or DBA-style SQL performance work. Experience working alongside or managing consultancy partners. Background in high-data-volume or regulated industries. Why Join Us? Help choose and implement the tooling that will define our future. A strategic, hands-on role that truly shapes our platform. The chance to modernise a growing data function from the ground up. A team of 8 (4 engineers) with consultancy support and room to scale. Long-term career impact: your work sets the foundation for the next phase of our data maturity.