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 high-impact 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:

- Executive KPI dashboards & scorecards

- Enterprise data models & semantic layer

- Automated MIS & report distribution

- Sales, service & churn analytics suites

- Governed self-serve analytics environment

AI-Enhanced BI Deliverables:

- BI Copilot - NL2SQL over the semantic layer AI

- Conversational data explorer for business users AI

- Automated insight & narrative generation AI

- Employee knowledge assistant (RAG) AI

- Anomaly detection & proactive alerting agents AI

Required Technical Skills - Core BI & Data (Primary):

- 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):

- 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.

- 2-5 years of professional 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.