Senior Databricks Engineer, Analytics

• Work with reporting owners to document KPI definitions, calculation rules, source mappings, dimensions, filters and acceptance criteria
• Analyse Power BI semantic models and DAX measures to understand authoritative reporting logic
• Develop reference SQL and test datasets; work with the Databricks engineer to translate approved logic into metric views and supporting queries
• Reconcile results across source data, reporting models and Genie answers, documenting and resolving discrepancies with the appropriate owner
• Test aggregation, distinct counts, ratios, date boundaries, missing values, duplicate records and differences in data refresh timing
• Create a benchmark question set with approved reference answers, tolerances and repeatable regression checks
• Assess answer relevance, table/chart consistency, document citations and behaviour when questions are ambiguous or unsupported
• Test that users receive only the results permitted by the agreed access model
• Coordinate user acceptance testing, track defects and prepare evidence for business sign-off
• Document KPI definitions, validation procedures and known limitations for handover

• Strong BI or analytics engineering experience; typically 4+ years with hands-on semantic modelling and data validation
• Advanced SQL and strong Power BI/DAX skills, including relationships, filter context, time intelligence and measure behaviour
• Experience reconciling numbers across reports or systems and tracing discrepancies to data, business definitions or calculation logic
• Understanding of dimensional modelling, fact-table grain, joins and additive/non-additive measures
• Ability to build repeatable data checks using SQL and a scripting or testing tool, such as Python
• Experience turning business requirements into testable acceptance criteria and supporting UAT
• English communication, strong attention to detail and confidence discussing KPI definitions with business stakeholders
• Preferred: Databricks SQL, Unity Catalog and metric views
• Preferred: Databricks Genie or other conversational analytics evaluation
• Preferred: Microsoft Fabric Lakehouse/Warehouse, semantic models and data pipelines
• Preferred: Power BI model metadata/TMDL and tools for inspecting DAX behaviour
• Preferred: Semantic model performance analysis and data quality automation
• Preferred: Telecom, subscription, sales or network reporting