Principal Engineering Manager

6 days ago


Bengaluru, Karnataka, India Microsoft Full time ₹ 12,00,000 - ₹ 30,00,000 per year

Microsoft's Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture. 

​​Within Azure Data, the business intelligence team builds and maintains Power BI which is the undisputed leader in BI tool in the industry today and serves as the bridge between data professionals & Office users. Power BI's core value proposition is to enable end users to get answers & insights from their data through data visualization.​ 

​​Within this organization, the Analysis Services Engine (AS) team builds and evolves the analytical database engine that is the core foundation behind the Power BI Semantic Models aka Datasets as well as SQL Server Analysis Services (SSAS) and Azure Analysis Services (AAS).  
 
Power BI continues to grow rapidly as one of the world's leading analytical SaaS platforms. SSAS remains a key pillar of the multi-billion-dollar SQL Server product line, while AAS stands out as one of the fastest-growing services in the Azure ecosystem. Together, these platforms enable lightning-fast, enterprise-grade analytics at global scale, empowering organizations everywhere to turn data into decisions. As adoption of the Analysis Services Engine expands across these products, our team is poised for an exciting and impactful future.  
 
As a Principal Engineering Manager, you will lead a high-impact team focused on elevating the quality and reliability of Analysis Services (AS). You will own robust testing strategies, AI-powered automation frameworks, and modern testing architectures. You will drive the adoption of data-driven quality practices and foster a culture of accountability, model, coach and care. In parallel, you will be part of development of secure, scalable engineering systems that enhance productivity and ensure compliance. This includes promoting GenAI integration, secure design principles, and tool innovation to support efficient engineering systems workflows. You will foster inclusive collaboration across disciplines and geographies, ensuring alignment on goals and delivery timelines through transparent communication and shared tooling. The role demands metric-based execution and continuous tracking of success indicators to guide team priorities and outcomes.  


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