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Agilon Health partners with community-based physicians to transform care delivery for seniors. Our platform and care model help physicians move beyond fee-for-service constraints and deliver coordinated, value-based care. Insights Engineering is central to that mission. In this role, you will turn complex healthcare data into trusted, actionable insights that improve outcomes and reduce medical waste. You will work cross-functionally with clinical, finance, operations, product, and technology teams to deliver analytics that drive better decisions.
Job Responsibility
Build and maintain high-quality, scalable data models and semantic layers for analytics use cases
Deliver end-to-end insight work: problem framing, analysis, visualization, and communication
Partner with Product, Clinical Analytics, Medical Economics, Finance, and Operations on key priorities
Apply and champion AI-enabled workflows to improve team productivity, insight velocity, and adoption of trusted analytics practices
Design intuitive dashboards and self-serve reporting experiences for business and clinical stakeholders
Improve data quality, documentation, and analytics standards across core reporting assets
Use hypothesis-driven analysis to identify opportunities to improve patient outcomes and reduce avoidable cost
Contribute to team best practices and support peers through collaboration and knowledge sharing
Requirements
5+ years of experience in analytics engineering, BI, or data-focused analytics roles
Strong SQL proficiency
experience with cloud data warehouses (Snowflake preferred)
Experience with data modeling and transformation frameworks (dbt preferred)
Experience building dashboards in Sigma, Tableau, Power BI, or similar tools
Strong analytical and problem-solving skills with attention to data quality and business context
Ability to translate ambiguous business questions into clear analytical plans
Strong written and verbal communication skills for technical and non-technical audiences
Bachelor's degree or equivalent practical experience
Nice to have
Healthcare analytics experience, especially in risk adjustment, clinical quality, utilization, attribution, or medical economics
Familiarity with healthcare data structures and longitudinal/member-level analysis
Python (or similar language) for automation or advanced analytics
Comfort operating in a fast-paced, evolving environment with a high degree of ownership