Senior Power BI Engineer

Job Description:-

Must Have Technical/Functional Skills

• Expert-level knowledge of dashboard design principles for effective data analysis and storytelling.
• Advanced proficiency in DAX and Power BI semantic modeling.
• Strong experience with dataflows and Microsoft Fabric environments.
• Familiarity with Databricks - Databricks One, Lakehouse, AI/BI Genie and Dashboards is a plus.
• Proven ability to perform complex ad hoc analysis using Excel and Azure SQL databases.
• Deep understanding of enterprise data warehouse environments, including data architecture, integration, and governance.
• Ability to extract, interpret, and translate complex business requirements into comprehensive analytics solutions, proactively identifying gaps and proposing enhancements.
• Demonstrated leadership in mentoring junior team members and fostering a culture of continuous learning.
• Experience managing reporting product backlogs, defining requirements, and aligning analytics deliverables with strategic business objectives.
• Strong collaboration skills and ability to drive cross-functional teams.
• Expertise in the Microsoft data stack and advanced SQL programming for large-scale data processing.
• Excellent written and verbal communication skills, with the ability to present complex data insights to technical and non-technical audiences.

Experience Required

• Minimum 5 years of hands-on experience with Power BI (required); experience with Tableau is a desired.
• 7+ years of experience in business intelligence and analytics.
• 5+ years of experience with relational databases and dimensional modeling.
• 5+ years of experience using SQL Server Management Studio (SSMS).
• Experience with Microsoft Azure services (e.g., Data Factory, Data Warehouse).
• Experience collaborating with product owners and contributing to Agile development processes.
• Background in healthcare, especially in Home Health, Hospice, or Rehabilitation services.
• Experience mentoring or training junior developers in Power BI and data visualization best practices.
• Experience working within large-scale enterprise data warehouse environments, including navigating complex data ecosystems, integrating diverse data sources, and ensuring data integrity across systems.