Senior Analytics & AI Engineer (Power BI, Data Platforms & Azure AI)
- Bengaluru
- Monterrey
- Montevideo
- Remote.Argentina
- Remote.Brazil
- Remote.Colombia
- Rosario
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Position overview
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.
Requirements
- 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.
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