Power BI

Location: Gurugram/Noida

JD

Key Responsibilities

• Design, develop, and maintain Power BI reports, dashboards, and semantic models optimized for performance and scalability.
• Perform Power BI data modeling, including star schema design, relationships, and measures using DAX.
• Lead performance tuning and optimization, including query reduction, model optimization, and report rendering improvements.
• Implement Power BI Embedded solutions using Power BI Embedded APIs, supporting custom application integration.
• Work with embedded tokens and authentication mechanisms to securely expose Power BI content in custom applications.
• Collaborate with UI and front end teams to enable custom UI integration with embedded Power BI reports and visuals.
• Design and manage Row Level Security (RLS) models to enforce data access rules aligned with business requirements.
• Implement and maintain incremental refresh strategies for large datasets to optimize refresh times and resource usage.
• Develop and maintain Power Query (M) scripts for data transformation and ingestion.
• Work with Enhanced XMLA endpoints for advanced dataset operations, deployments, and automation scenarios.
• Support project and application integration, ensuring Power BI artifacts align with enterprise architecture and DevOps practices.
• Participate in design reviews, troubleshooting, and production support as required.

Required Skills

Technical Skills

• Strong hands on experience with Power BI data modeling
• Knowledge on Python
• Proven expertise in performance tuning and optimization in Power BI
• Solid understanding of Row Level Security (RLS) concepts and implementations
• Hands on experience with Incremental Refresh
• Strong knowledge of Power Query (M scripting)

Experience working with Enhanced XMLA scripting

• Experience with enterprise project integration involving Power BI
• Nice to Have
• Experience with Azure services (Azure SQL, Azure Data Factory, Azure Synapse)
• Knowledge of CI/CD pipelines for Power BI deployments
• Familiarity with version control and automated release processes
• Exposure to large scale enterprise data environments