Senior Data Analyst — Power BI / Microsoft Fabric | Active Secret

About this role

Senior Data Analyst — Power BI & Microsoft Fabric | Active Secret Location: Remote — U.S. Clearance: Active Secret Why This Role Rackner is seeking a Senior Data Analyst to help modernize enterprise analytics within a Microsoft data environment. This is more than a dashboard-development role. You’ll help shape the semantic models, KPI standards, reporting products, security controls, and reusable analytics foundations that enable leaders and operational teams to make trusted decisions.

Working across business stakeholders, data engineering, governance, and technical teams, you’ll have the opportunity to influence how analytics products are designed, modernized, governed, and adopted across the organization. If you’ve built strong Power BI solutions and are ready for broader ownership, this role offers the opportunity to influence the analytics architecture, standards, modernization strategy, and product portfolio behind those solutions—not just the final visualization.

What You’ll Do Lead the design and modernization of enterprise analytics and business intelligence solutions using Power BI and Microsoft Fabric Shape governed semantic models, shared datasets, KPI definitions, and reusable analytical components Build and optimize executive, operational, and compliance reporting that supports mission and business decisions Modernize legacy reporting by evaluating usage, redundancy, technical debt, performance, and opportunities for consolidation Standardize fragmented dashboards and reports into scalable enterprise analytics products Develop advanced DAX measures, calculations, business logic, and Power Query transformations Secure analytics products through row-level and object-level access controls aligned with data-governance requirements Enable self-service analytics while maintaining appropriate security, governance, and data-quality controls Assess Power BI licensing, capacity, and deployment approaches based on organizational needs Translate stakeholder needs into analytical requirements, functional specifications, user stories, and acceptance criteria Partner across data engineering, governance, application, and source-system teams to move analytics products from requirements through adoption Solve complex semantic-modeling, reporting, performance, reconciliation, and data-quality challenges Influence analytics strategy, roadmap decisions, portfolio priorities, and reporting standards Explore forecasting, predictive analytics, and AI-assisted analytics where they provide practical value Support demonstrations, user acceptance testing, documentation, and adoption of analytics products What Makes Someone Successful Here We’re most interested in candidates who can discuss specific work they personally owned, the decisions they made, and the outcomes they helped deliver.