Principal BI Architect – Agentic BI

We are seeking a hands-on Manager – BI & Analytics to lead the design, development, and delivery of enterprise-scale BI and analytics solutions. The ideal candidate will have deep expertise in Power BI, Tableau, SQL, MS Fabric,, Snowflake, and Databricks , combined with a strong understanding of modern GenAI, LLM, and Agentic BI capabilities. This is a hands-on Manager role . The Manager will not only lead teams and client engagements but will also remain deeply involved in solution architecture, data modeling, BI development, performance optimization, technical problem-solving, and emerging Agentic BI initiatives. The role requires someone who can bridge business requirements, BI engineering, modern data platforms, and AI-driven analytics to deliver measurable business impact. Key Responsibilities: . BI Leadership: Lead the design and development of enterprise BI solutions while remaining hands-on with complex dashboards, reports, semantic models etc. Personally troubleshoot complex BI performance, data modeling, refresh, and scalability issues. Establish reusable BI frameworks, development standards, visualization best practices, and governance practices, while reviewing solutions developed by BI engineers and analysts and providing technical direction. 2. Data Modeling, SQL & Modern Data Platforms: Design scalable analytical data models and reporting architectures across Snowflake, Databricks, Azure SQL, and other enterprise data platforms. Write and optimize complex SQL for data extraction, transformation, analysis, and BI consumption. Work hands-on with Snowflake for data warehousing, analytical workloads, performance optimization, and BI integration, as well as Databricks/Lakehouse, Spark, and PySpark to develop and consume scalable analytical datasets. Collaborate with Data Engineering teams to improve ETL/ELT pipelines, data quality, data lineage, and source-to-report consistency. 3. GenAI & LLM-Powered Analytics: Lead and contribute hands-on to GenAI and LLM-powered BI initiatives, including natural-language analytics, automated insight generation, narrative reporting, and conversational BI. Identify opportunities to leverage LLMs and Python-based AI automation to improve analytics processes and reduce manual reporting effort. Partner with Data Science and AI Engineering teams to integrate LLM capabilities with enterprise data, semantic models, and BI applications, while evaluating emerging GenAI technologies and determining where they can deliver meaningful business value. 4. Agentic BI: Drive the development of Agentic BI solutions that can interpret business questions, interact with semantic models and enterprise data sources, perform multi-step analysis, and generate actionable recommendations. Design use cases where AI agents can interact with Power BI semantic models, Snowflake, Databricks, SQL databases, APIs, and business applications. Explore agent-driven capabilities such as automated root-cause analysis, anomaly investigation, predictive insights, and next-best-action recommendations, while establishing appropriate validation, evaluation, security, governance, and human-in-the-loop controls for AI-generated business insights. 5. End-to-End Solution Ownership: Own BI and analytics initiatives from business requirement discovery through solution design, development, testing, deployment, and adoption. Translate complex business problems into scalable analytical and AI-driven solutions by defining KPIs, metrics, data requirements, analytical approaches, and solution architecture. Ensure solutions are designed for performance, scalability, maintainability, security, and business usability throughout the delivery lifecycle. 6. Client & Stakeholder Leadership: Act as a senior technical and business-facing leader for BI and analytics engagements, working directly with business and client stakeholders to understand strategic objectives and translate them into data and analytics solutions. Present complex analytical