Required Skills

azurepower bipythonsql

Job Description

Position overview: We are seeking a Senior Analytics \& AI Engineer to help optimize and evolve enterprise analytics solutions built on Power BI, SQL Server, and modern data platforms while enabling AI\-driven analytics experiences using Azure AI technologies.
The role combines strong expertise in semantic models, data engineering, reporting performance, and analytics architecture with practical experience building AI\-powered solutions such as copilots, AI agents, Text\-to\-SQL, and conversational analytics.
The ideal candidate is equally comfortable optimizing Power BI semantic models, designing scalable analytical datasets, and integrating AI capabilities on top of enterprise analytics platforms.

Responsibilities: Design and optimize Power BI semantic models for large\-scale analytical workloads.
Improve report performance through DirectQuery optimization, aggregations, caching strategies, and semantic model tuning.
Develop and maintain dimensional models, analytical datasets, and data integration pipelines.
Support AI\-driven analytics initiatives by exposing business metadata, semantic definitions, and governed datasets.
Design and implement AI\-powered analytics solutions using Azure OpenAI and Azure AI Foundry.
Build Text\-to\-SQL and Text\-to\-DAX capabilities over enterprise analytics platforms.
Develop grounding, metadata enrichment, and retrieval strategies for AI Agents.
Implement observability, evaluation, and guardrail mechanisms for AI solutions.
Collaborate with architects and business stakeholders to define future\-state analytics and AI architectures.

5\+ years of experience in BI, Analytics Engineering, Data Engineering, or Analytics Solutions.
Advanced Power BI and semantic model design experience.
Strong SQL Server and T\-SQL skills.
Strong dimensional modeling and data warehousing knowledge.
Experience optimizing DirectQuery, Import, and hybrid reporting architectures.
Strong DAX and Power Query skills.
Experience with ETL/ELT, data integration, and analytical platform design.
Python development experience.
Experience working with LLMs, Azure OpenAI, or AI\-assisted analytics solutions.
Understanding of RAG, grounding, prompt engineering, and AI evaluation concepts.

Nice to have: Microsoft Fabric (Lakehouse, Warehouse, Semantic Models, Dataflows).
Azure AI Foundry.
Text\-to\-SQL or Text\-to\-DAX implementations.
Copilot Studio or Fabric Data Agents.
Semantic Kernel, LangGraph, AutoGen, or similar frameworks.
Tabular Editor and SSAS Tabular.
Enterprise metadata, governance, and lineage solutions.
Experience supporting conversational analytics or AI Agents over BI platforms.