Director of Analytics Engineering

<div class="content-intro"><p><strong>About Us</strong></p> <p>Ennoble Care is a mobile primary care, palliative care, and hospice service provider with patients in New York, New Jersey, Maryland, DC, Virginia, Oklahoma, Kansas, Pennsylvania, Texas, Florida, and Georgia. Ennoble Care’s clinicians go to the home of the patient, providing continuum of care for those with chronic conditions and limited mobility. Ennoble Care offers a variety of programs including, remote patient monitoring, behavioral health management, and chronic care management, to ensure that our patients receive the highest quality of care by a team they know and trust. We seek individuals who are driven to make a difference and embody our motto, “To Care is an Honor.” Join Ennoble Care today!</p></div><p><strong>ABOUT THE ROLE</strong></p> <p>We’re hiring a hands-on technical leader to strengthen and expand Ennoble’s ACO analytics data infrastructure. You’ll own the design of a unified data platform integrating our Medicare claims feeds (DPC, CCLF, BCDA), CMS alignment and benchmark files, in-house clinical systems, and external vendor data into a single, accurate, queryable layer. We expect this person to bring engineering rigor and AI-augmented practices to our team.</p> <p>This candidate will be our internal thought-leader on AI-augmented data engineering: LLM coding assistants, automated QA, autonomous data-quality agents, intelligent cross-source reconciliation, MCP servers as needed, and conversational query layers. This candidate will lead our large-scale analytics platform and web app rollout as the team's analytical foundation. Individual contributor today, with a clear path to building and leading an engineering team as scope grows.</p> <p><strong>WHAT YOU'LL DO</strong></p> <ul> <li><strong>Strengthen and expand our analytics data warehouse infrastructure </strong></li> <li><strong>Lead AI-augmented engineering adoption: </strong>codify patterns for LLM coding assistants (e.g., Claude Code under BAA), agentic QA, autonomous data-quality monitoring agents, and conversational query layers</li> <li><strong>Own data accuracy and reconciliation — </strong>build validation, monitoring, and audit infrastructure that catches issues before they reach reporting or CMS submissions — extending our ~158-object audit and observability framework (ADF run logging, MBI crosswalk QA, DPC parity harness, transactional refresh with auto-rollback)</li> <li><strong>Partner with analytics leads (MSSP, ACO REACH/LEAD, GUIDE, Quality, Dashboards) </strong>to ensure infrastructure meets internal and external reporting requirements and advanced downstream modeling needs</li> <li><strong>Lead large-scale analytics platform and web app implementat