Key Responsibilities
• Partner with business stakeholders to capture, challenge and document data and reporting requirements, translating them into clear analytical specifications.
• Build, maintain and optimise data models, reports and dashboards within Microsoft Fabric (Lakehouse, Data Warehouse, Power BI, Dataflows and Pipelines).
• Write and optimise SQL to extract, transform and validate data from multiple source systems.
• Deliver self-serve reporting and analysis that gives commercial, operational and finance teams a single, trusted view of performance.
• Analyse trends, identify opportunities and root-cause issues, and present findings and recommendations to both technical and non-technical audiences.
• Define and document data definitions, KPIs and business logic, and support data quality and governance standards.
• Build, manage and maintain the data catalogue documenting data assets, definitions, lineage and ownership to improve data discoverability and trust across the business.
• Work with data engineers and the wider data team to improve the analytics platform, data pipelines and ways of working.
Required Skills & Experience
• Proven experience as a Data / Business Analyst delivering reporting and analytics in a commercial environment.
• Hands-on experience with Microsoft Fabric – e.g. Lakehouse, Data Warehouse, Power BI, Dataflows Gen2 and Pipelines.
• Experience migrating data and analytics workloads from Azure Synapse and SQL Server 2019 to a modern platform such as Microsoft Fabric.
• Strong SQL skills, with the ability to write efficient queries against large datasets.
• Strong Power BI skills, including data modelling and DAX, to build clear and performant dashboards.
• Excellent requirements-gathering and stakeholder-management skills, with the ability to translate business questions into analytical solutions.
• Strong analytical and problem-solving skills and high attention to detail.
• Confident communicator, able to explain data and insight clearly to non-technical audiences.
Desirable (Nice to Have)
• Experience in grocery, food retail or FMCG, and an understanding of the data that drives them (e.g. sales, ranging, stock, supply chain, promotions and loyalty).
• Familiarity with the wider Microsoft data stack (Azure, Power Platform).
• Experience with Python for data analysis or automation.
• Understanding of data governance, data quality and modelling best practices.