À propos du poste
Power BI Engineer
- Microsoft Fabric hands-on experience, including workspaces, capacities, OneLake, lakehouse and warehouse artifacts, and how a semantic model sits on top of them.
- Power BI Desktop and the Power BI service to a production standard: model, report, publish, refresh, and share.
- DAX including calculated measures, CALCULATE and filter context, time intelligence, and variables for readability.
- Power Query and the M language for shaping, merging, and cleansing data at model load.
- Star schema modeling: fact and dimension tables, relationship cardinality and direction, role-playing dimensions, and why flattened wide tables cause problems later.
- SQL to a working level for profiling source data and validating report figures against the underlying tables.
- Report and dashboard design fundamentals: appropriate visual selection, layout, consistent formatting, conditional formatting, bookmarks, and drillthrough.
- Row-level security implementation and testing, including dynamic security driven by the signed-in user.
- Report validation discipline: reconciling every published figure to a source of truth and documenting the check.
Preferred:
- Fabric semantic model storage modes, particularly Direct Lake, and the practical differences between Direct Lake, Import, and DirectQuery.
- Refresh configuration and troubleshooting, covering scheduled refresh, incremental refresh, gateways, and credential management.
- Tabular Editor, DAX Studio, and the Best Practice Analyzer for model development and performance work.
- Fabric deployment pipelines, workspace app lifecycle, and Git integration for reports and semantic models.
- Paginated reports in Power BI Report Builder for pixel-perfect and print output.
Microsoft certification PL-300, and DP-600 for Fabric analytics engineering.