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Data Analytics
Responsibilities
- Design, develop, and maintain interactive dashboards and paginated reports in Power BI Desktop and publish to Power BI Service.
- Build robust semantic models; author efficient DAX measures and calculated columns for performance and accuracy.
- Create and manage Power Query (M) transformations and Dataflows for reusable, governed data preparation.
- Administer workspaces, datasets, gateways, refresh schedules, and deployment pipelines following best practices.
- Implement row-level security (RLS), object-level security (OLS), and enforce governance standards for data protection.
- Integrate Power BI solutions with Power Automate (flows) and Power Apps (canvas/model-driven apps) to enable analytics-driven workflows.
- Develop or extend custom visuals where required to meet advanced UI/UX needs.
- Write SQL for data extraction, shaping, and performance tuning; collaborate on ETL with data engineering teams.
- Conduct stakeholder workshops to gather requirements, map KPIs, and validate deliverables against business outcomes.
- Instrument usage analytics, monitor performance, and iterate on design for continuous improvement.
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Document solutions, standards, and handover materials; coach users through demos and training.
- Power BI Desktop & Power BI Service (hands-on).
- Advanced DAX authoring and performance optimization.
- Power Query (M) transformations and reusable Dataflows.
- Power Automate integration (triggered flows, approvals, notifications).
- Power Apps integration (canvas/model-driven) to complement BI workflows.
- Custom visual development and configuration.
- Strong SQL (T-SQL/ANSI SQL) for data modeling and tuning.
- Data modeling (star/snowflake), semantic layer design, and governance.
- Security: RLS/OLS, workspace roles, sensitivity labels, and tenant policies.
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