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Stellar Health is a venture-backed healthtech platform transforming primary care delivery by shifting from fee-for-service to value-based reimbursement. The company provides real-time patient information, practice staff activation, and outcome-based incentives to help providers deliver better care while reducing costs for payors.
As Senior Staff AI Data Engineer, you will lead the strategic evolution of AI-powered analytics and reporting at Stellar, alongside the data architecture that enables it. This is a high-impact, architect-mentor role where your influence extends across the entire analytics organization.
Key responsibilities include:
**AI for Analytics & Reporting:** Set the company-wide strategy for how AI reshapes analytics, reporting, and self-serve data access. Own tool selection, administration, and architecture for Claude on Snowflake, MCP servers, agent workflows, and IDE integrations. Design evaluation and guardrail systems to ensure reliability and governance. Define processes for proposing, governing, and shipping analytics use cases. Debug complex failures that span LLM, data modeling, and system design. Mentor analytics engineers and analysts on AI-assisted approaches. Lead external thought leadership through content and communication.
**Data Modeling & Architecture:** Partner with analytics engineering to extend dbt + Snowflake models for reporting, analytics, and AI consumption. Establish standards for model structure, grain, documentation, metrics, tests, and lineage. Lead the semantic and context layers—metric definitions, business context, and metadata that make both dashboards and agents trustworthy.
You'll be equally credible discussing strategic direction for AI in analytics and developing a new data model the next day. Your impact is measured by what the entire analytics organization can accomplish, not just individual contributions. Decisions have direct, long-term consequences for Stellar's operational capability.