Senior Databricks Genie and Analytics Engineer

Key

Responsibilities 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. Experience/Qualifications: 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. learn English communication, strong attention to detail and confidence discussing KPI definitions with business stakeholders. Preferred experience Databricks SQL, Unity Catalog and metric views. Databricks Genie or other conversational analytics evaluation. Microsoft Fabric Lakehouse/Warehouse, semantic models and data pipelines. Power BI model metadata/TMDL and tools for inspecting DAX behaviour. Semantic model performance analysis and data quality automation. Telecom, subscription, sales or network reporting. Direct Genie experience is useful but not mandatory for this role. Strong SQL, DAX and demonstrated reconciliation work are the priorities. Broader Fabric engineering may be added only if included in the agreed project scope.