Senior Product Manager I - Enterprise Analytics

About Stellar Health: Historically, US Healthcare has relied on a fee-for-service reimbursement system where providers are paid based on the quantity of patient visits and procedures, rather than the quality of health outcomes. At Stellar Health, we help primary care providers put patient health first. Our platform - a mix of technology, people, and analytics - supports providers at the point of care, delivering real-time patient information, activating practice staff, and empowering providers and care teams with incentives that reward the work they are already doing to keep patients healthy. Using the Stellar App, our web-based, point-of-care tool; practices receive a simple checklist of recommended actions that support the best quality care. Providers and care teams are then paid monthly for each action they complete, and Payors save money in reduced healthcare costs along the way. Stellar is a US-based Health-tech backed by Top VCs (General Atlantic, Point72, & Primary Venture Partners) with an established product & proven operating model. We’ve shown that we make a real difference for physician practices and their patients. About the position: Stellar Health is looking for a Product Manager to lead our Analytics Engineering team and own the end-to-end lifecycle of our data and reporting products. This team is the engine room of our data organization, responsible for the dbt models and Snowflake architecture that power every decision we make. In this role, you will be the functional lead for the squad’s output, ensuring that our technical roadmap is perfectly synced with the business’s most pressing needs. You aren't just managing a backlog; you are the Product Owner of our Analytics Portfolio. You will own the "front-end" design and strategy for all dashboards and reports, ensuring they are intuitive, high-quality, and actionable. Crucially, you will drive consistent definitions across the organization, connecting our data models directly to business operations. You will also "shift left," collaborating with other Product squads to ensure underlying system architectures meet analytics needs before a single line of code is written. What you’ll do: - Drive the Analytics Engineering Roadmap: Serve as the functional lead for the AE squad; manage the backlog, lead sprint ceremonies, and ensure the team is focused on the highest-leverage modeling work. - Define Data as a Product: Own the requirement development for our analytics layers, ensuring dbt models and Snowflake structures are treated as curated products with high standards for uptime, documentation, and usability. - Standardize Business Logic: Drive the creation and maintenance of consistent data definitions across the company. You ensure that metrics are defined once in the modeling layer and used everywhere. - Support QA and Data Validation: Act as a final gate for quality; you will perform and coordinate QA on new data models and reports to ensure they meet business requirements and maintain high data integrity. - Perform Exploratory Analysis: Conduct ad-hoc analysis to validate assumptions, investigate data discrepancies, and help the team understand the impact of new data models on business KPIs. - Own the "Front-End" Data Portfolio: Lead the design, UX, and strategy for our internal and external reporting suites (Tableau/Looker). You define the standards for how data is visualized and consumed. - Operationalize Data via Reverse ETL: Oversee the integration of analytics data back into business systems (e.g., Salesforce, Customer.io http://Customer.io) via Data Contracts to ensure integrations are reliable and resilient. - Collaborate Across Product Squads: Act as the "voice of data" during the upstream product development process, ensuring that new features are built to support robust downstream analytics. You should have: - 5+ years of Product Management experience, specifically within a data-heavy environment (Analytics, BI, or Data Platforms). - The "Data-as-a-P