Data Engineering Lead

- Own the data warehouse schema, lakehouse design, and core data models - Translate business requirements into pragmatic, scalable data architecture decisions - Define, implement, and maintain data contracts aligned to business domains - Establish data quality, observability, and SLA frameworks - Design and evolve scalable data pipelines using Microsoft Fabric Pipelines, Azure Data Factory, and PySpark / Python Fabric Notebooks - Implement and maintain a medallion lakehouse architecture using OneLake and Fabric Warehouses - Ensure Direct Lake-ready semantic models for analytics - Lead incident management, root cause analysis, and data issue post-mortems - Enable self-service analytics through governed Power BI datasets - Support and guide the production of trusted Power BI reporting using data contracts - Define engineering standards and review pull requests - Mentor and develop 2-4 data and cloud engineers - Drive the data and warehouse roadmap alongside the Digital Transformation Director - Champion CI/CD, secure secret management, and software engineering best practices - Deliver and continuously refine a Microsoft Fabric data warehouse supporting business-led decision making - Integrate data from diverse sources including APIs, files, databases, and cloud platforms - Establish data contracts as a core mechanism for trusted analytics - Scale Power BI reporting using standardised, high-quality data products - Provide clear, motivating leadership to direct reports - Conduct regular 1:1s, performance reviews, and development planning - Recruit, onboard, and develop a high-performing data engineering team - Ensure compliance with company policies, legal obligations, and operating procedures