Bitwise
Fabric Data Agent Lead
Skills
24 days ago
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Important information
Contract type:
Permanent
Salary:
$150,000 – $180,000 / year
Location:
Grand Rapids, MI, USA
Work mode:
Onsite
Published on:
4 October 2026
What they need
About us
Bitwise leverages its deep technological expertise to develop solutions for their clients' most complex business problems. Over 25+ years of consistently bringing high-performance solutions to our market leading clients in diverse industries across the world, guarantees that our tools, processes and people are above par to offer singular value to every engagement. Partnerships with Bitwise yield long term business gains, as clients deliver more and deliver faster, because they are ahead of the curve in a dynamic business landscape. This is made possible through our data driven business insights and our innovative and agile methodologies.
Our Core Values - Excellence, Compassion, Open-Mindedness, Mutual Respect, Ownership, Integrity and Belongingness
Job Description
Role Objective - Lead discovery sessions with business SMEs to design, architect, and deploy intelligent Fabric Data Agents grounded in Power BI semantic models. Direct/ guide other technical resources
Technical - Good understanding of Power BI semantic models (star schemas, explicit DAX, metadata) in Fabric to ensure they are fully queryable and reliable for LLMs. This skill set can be complemented by other resources.
-Demonstrable hands-on experience across the end-to-end Fabric data platform, with strong data engineering depth
-Familiarity with Fabric's integration points into Azure native AI tooling
AI Orchestration - Build and orchestrate conversational flows using Copilot Studio, advanced system prompt engineering, and grounding/RAG techniques.
Governance & Safety - Implement strict Responsible AI criteria, content filtering, and Row-Level Security (RLS) to prevent hallucinations and unauthorized data exposure.
Testing & Delivery - Drive end-to-end testing, benchmarking agent response accuracy against known business data truths prior to deployment.
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