Summary:
The GenBI Engineer plays a pivotal role in bridging advanced artificial intelligence with business intelligence enabling intelligent self-service analytics through AI-powered data platforms. This position is critical in designing and optimizing semantic models and data sets for large language model (LLM) consumption ensuring seamless natural language interactions accurate query interpretation and reliable automated insights. By integrating AI capabilities into Power BI and AWS QuickSight the engineer enhances the analytical experience for business users drives data democratization and ensures robust data governance. The role demands a blend of deep technical expertise in BI tools AI/ML fundamentals and a strategic mindset to future-proof analytics infrastructure.
Responsibilities:
- Design and optimize Power BI Semantic Models or AWS QuickSight Data Sets specifically tailored for LLM consumption emphasizing clear naming synonym mapping and metadata hierarchies.
- Develop and refine prompts to guide AI agents in delivering precise actionable insights from BI data.
- Configure and tune linguistic schemas and synonym sets to maximize the accuracy and usability of Chat with Data capabilities.
- Implement AI-driven automation using Copilot (Fabric) or Amazon Q to generate executive summaries narrative insights and anomaly detection reports.
- Utilize generative AI to accelerate the creation of complex DAX measures and SQL queries while upholding strict validation and peer-review processes.
- Partner with Data Engineering teams to enforce data quality privacy and security standards mitigating risks of AI hallucinations and unauthorized data usage in model training.
Requirements
- Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight.
- Solid understanding of LLMs including how they interpret structured data vector embeddings for RAG-based analytics MCP architecture and tokenization.
- Expertise in semantic modeling to empower end users in building self-service reports.
- Advanced skills in either Power BI (DAX Power Query) or AWS QuickSight (Calculated Fields SPICE).
- Mastery in writing and optimizing complex SQL queries to support AI-ready data pipelines.
Additional Details:
Experience: 8-10 years
Must-Have: Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight
Gen BI tools: Power BI Copilot (Fabric) or Amazon Q in QuickSight
Location: Bangalore
Mode of work: Hybrid
Notice Period: Immediate to 20 days
Required Skills:
Summary: The GenBI Engineer plays a pivotal role in bridging advanced artificial intelligence with business intelligence enabling intelligent self-service analytics through AI-powered data platforms. This position is critical in designing and optimizing semantic models and data sets for large language model (LLM) consumption ensuring seamless natural language interactions accurate query interpretation and reliable automated insights. By integrating AI capabilities into Power BI and AWS QuickSight the engineer enhances the analytical experience for business users drives data democratization and ensures robust data governance. The role demands a blend of deep technical expertise in BI tools AI/ML fundamentals and a strategic mindset to future-proof analytics infrastructure. Responsibilities: Design and optimize Power BI Semantic Models or AWS QuickSight Data Sets specifically tailored for LLM consumption emphasizing clear naming synonym mapping and metadata hierarchies. Develop and refine prompts to guide AI agents in delivering precise actionable insights from BI data. Configure and tune linguistic schemas and synonym sets to maximize the accuracy and usability of Chat with Data capabilities. Implement AI-driven automation using Copilot (Fabric) or Amazon Q to generate executive summaries narrative insights and anomaly detection reports. Utilize generative AI to accelerate the creation of complex DAX measures and SQL queries while upholding strict validation and peer-review processes. Partner with Data Engineering teams to enforce data quality privacy and security standards mitigating risks of AI hallucinations and unauthorized data usage in model training. Requirements Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight. Solid understanding of LLMs including how they interpret structured data vector embeddings for RAG-based analytics MCP architecture and tokenization. Expertise in semantic modeling to empower end users in building self-service reports. Advanced skills in either Power BI (DAX Power Query) or AWS QuickSight (Calculated Fields SPICE). Mastery in writing and optimizing complex SQL queries to support AI-ready data pipelines. Additional Details: Experience: 8-10 years Must-Have: Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight Gen BI tools: Power BI Copilot (Fabric) or Amazon Q in QuickSight Location: Bangalore Mode of work: Hybrid Notice Period: Immediate to 20 days
Required Education:
Graduate
Summary:The GenBI Engineer plays a pivotal role in bridging advanced artificial intelligence with business intelligence enabling intelligent self-service analytics through AI-powered data platforms. This position is critical in designing and optimizing semantic models and data sets for large languag...
Summary:
The GenBI Engineer plays a pivotal role in bridging advanced artificial intelligence with business intelligence enabling intelligent self-service analytics through AI-powered data platforms. This position is critical in designing and optimizing semantic models and data sets for large language model (LLM) consumption ensuring seamless natural language interactions accurate query interpretation and reliable automated insights. By integrating AI capabilities into Power BI and AWS QuickSight the engineer enhances the analytical experience for business users drives data democratization and ensures robust data governance. The role demands a blend of deep technical expertise in BI tools AI/ML fundamentals and a strategic mindset to future-proof analytics infrastructure.
Responsibilities:
- Design and optimize Power BI Semantic Models or AWS QuickSight Data Sets specifically tailored for LLM consumption emphasizing clear naming synonym mapping and metadata hierarchies.
- Develop and refine prompts to guide AI agents in delivering precise actionable insights from BI data.
- Configure and tune linguistic schemas and synonym sets to maximize the accuracy and usability of Chat with Data capabilities.
- Implement AI-driven automation using Copilot (Fabric) or Amazon Q to generate executive summaries narrative insights and anomaly detection reports.
- Utilize generative AI to accelerate the creation of complex DAX measures and SQL queries while upholding strict validation and peer-review processes.
- Partner with Data Engineering teams to enforce data quality privacy and security standards mitigating risks of AI hallucinations and unauthorized data usage in model training.
Requirements
- Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight.
- Solid understanding of LLMs including how they interpret structured data vector embeddings for RAG-based analytics MCP architecture and tokenization.
- Expertise in semantic modeling to empower end users in building self-service reports.
- Advanced skills in either Power BI (DAX Power Query) or AWS QuickSight (Calculated Fields SPICE).
- Mastery in writing and optimizing complex SQL queries to support AI-ready data pipelines.
Additional Details:
Experience: 8-10 years
Must-Have: Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight
Gen BI tools: Power BI Copilot (Fabric) or Amazon Q in QuickSight
Location: Bangalore
Mode of work: Hybrid
Notice Period: Immediate to 20 days
Required Skills:
Summary: The GenBI Engineer plays a pivotal role in bridging advanced artificial intelligence with business intelligence enabling intelligent self-service analytics through AI-powered data platforms. This position is critical in designing and optimizing semantic models and data sets for large language model (LLM) consumption ensuring seamless natural language interactions accurate query interpretation and reliable automated insights. By integrating AI capabilities into Power BI and AWS QuickSight the engineer enhances the analytical experience for business users drives data democratization and ensures robust data governance. The role demands a blend of deep technical expertise in BI tools AI/ML fundamentals and a strategic mindset to future-proof analytics infrastructure. Responsibilities: Design and optimize Power BI Semantic Models or AWS QuickSight Data Sets specifically tailored for LLM consumption emphasizing clear naming synonym mapping and metadata hierarchies. Develop and refine prompts to guide AI agents in delivering precise actionable insights from BI data. Configure and tune linguistic schemas and synonym sets to maximize the accuracy and usability of Chat with Data capabilities. Implement AI-driven automation using Copilot (Fabric) or Amazon Q to generate executive summaries narrative insights and anomaly detection reports. Utilize generative AI to accelerate the creation of complex DAX measures and SQL queries while upholding strict validation and peer-review processes. Partner with Data Engineering teams to enforce data quality privacy and security standards mitigating risks of AI hallucinations and unauthorized data usage in model training. Requirements Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight. Solid understanding of LLMs including how they interpret structured data vector embeddings for RAG-based analytics MCP architecture and tokenization. Expertise in semantic modeling to empower end users in building self-service reports. Advanced skills in either Power BI (DAX Power Query) or AWS QuickSight (Calculated Fields SPICE). Mastery in writing and optimizing complex SQL queries to support AI-ready data pipelines. Additional Details: Experience: 8-10 years Must-Have: Proficiency with Gen BI tools such as Power BI Copilot (Fabric) or Amazon Q in QuickSight Gen BI tools: Power BI Copilot (Fabric) or Amazon Q in QuickSight Location: Bangalore Mode of work: Hybrid Notice Period: Immediate to 20 days
Required Education:
Graduate
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4 hours ago
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