Senior BI Engineer (Analytics & Agentic AI) (Noida)

Senior BI Engineer Analytics & Agentic AI Role Overview We are looking for a hands-on Senior BI Engineer to strengthen our established Business Intelligence practice. Your primary mandate is core BI engineering: designing robust data models and semantic layers, building highimpact dashboards and executive reporting, and owning the ETL/ELT pipelines that keep enterprise analytics accurate, fast, and trusted. The remaining is where this role stands apart: our BI team has already shipped agentic AI applications in production and you will help extend this AI layer on top of our BI stack, making analytics conversational, proactive, and self-serve for business users and executives. Who Thrives Here - BI engineers who treat data models and dashboards as products governed, performant, and trusted by leadership. - SQL-first thinkers with strong DAX / semantic-modeling instincts and an eye for clean visual storytelling. - Self-starters who can take a vague business question and ship a working report, model, or copilot. - Curious technologists excited to bring LLM-powered experiences into the BI workflows they already master. Core BI Deliverables AI-Enhanced BI Deliverables Executive KPI dashboards & scorecards BI Copilot NL2SQL over the semantic layer AI Enterprise data models & semantic layer Conversational data explorer for business users AI Automated MIS & report distribution Automated insight & narrative generation AI Sales, service & churn analytics suites Employee knowledge assistant (RAG) AI Governed self-serve analytics environment Anomaly detection & proactive alerting agents AI Required Technical Skills Core BI & Data (primary) Skill Level / Notes SQL / T-SQL (Advanced) Complex queries, stored procedures, window functions, performance tuning SQL Server Data warehousing, indexing, execution plans, partitioning Snowflake Data warehousing, indexing, execution plans, Task Scheduler, Data Processing Power BI (Advanced) DAX, Power Query (M), semantic models, RLS, deployment pipelines Data Modeling Kimball dimensional modeling, star schema, fact/dimension design ETL / ELT Azure Data Factory, Fabric Dataflows, SSIS (legacy),Fivetran, incremental loads Reporting & Visualization Dashboard design, MIS automation, data storytelling and Tableau Azure Data Stack Fabric / Synapse, Blob Storage, Azure SQL, gateways Excel (Advanced) Power Pivot, complex analysis still the language of the business Agentic AI & LLMs (secondary) Skill Level / Notes LLM APIs Current frontier models OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI NL2SQL & BI Copilots Schema-aware SQL generation, semantic-layer grounding RAG Fundamentals Embeddings, vector stores (e.g., Azure AI Search, Chroma, FAISS), chunking Agent Frameworks LangGraph / LangChain; structured tool & function calling; MCP awareness Python (Proficient) FastAPI basics, data manipulation (pandas), API integration Prompt Engineering & Evaluation Prompt versioning, guardrails, hallucination detection, accuracy testing Qualifications - Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field. - 25 years of skilled experience in Business Intelligence, analytics, or data engineering roles. - Portfolio of production BI deliverables dashboards, semantic models, or reporting platforms in real business use. - Hands-on exposure to LLM-powered applications (NL2SQL, RAG, or copilots) production experience a strong plus. - Strong fundamentals: data modeling, clean SQL, testing, and documentation discipline. - Proven experience working with enterprise data environments and stakeholder-facing delivery. .