Director of Analytics Engineering

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!

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.

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.

• →Strengthen and expand our analytics data warehouse infrastructure
• →Lead AI-augmented engineering adoption: codify patterns for LLM coding assistants (e.g., Claude Code under BAA), agentic QA, autonomous data-quality monitoring agents, and conversational query layers
• →Own data accuracy and reconciliation — 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)
• →Partner with analytics leads (MSSP, ACO REACH/LEAD, GUIDE, Quality, Dashboards) to ensure infrastructure meets internal and external reporting requirements and advanced downstream modeling needs
• →Lead large-scale analytics platform and web app implementation, integration, and maintenance
• →Collaborate closely with IT and Engineering on tooling standards, organizational approvals, and security requirements (BAA scope, Microsoft Entra identity scoping, PHI/PII suppression, Azure SQL firewall)

• Data engineering depth: Strong hands-on experience with cloud-based analytics infrastructure and production data pipelines
• Platform: Microsoft Azure — incl. Azure SQL, Azure Data Factory, Azure DevOps, GitHub, Azure Blob Storage, Azure Databricks experience a strong plus
• SQL & Python: Expert T-SQL; Python proficient for ingestion utilities, internal web apps, and AI-agent tooling
• Data modeling: Experience designing unified/canonical models across heterogeneous source systems
• Data integrity: Demonstrated validation, reconciliation, and audit framework design — especially where discrepancies have material downstream impact
• Healthcare data: Familiarity with Medicare claims (CCLF, DPC, BCDA or similar) and/or risk-based contracting strongly preferred
• AI fluency: Track record using LLM-based tools (e.g., Claude Code, Copilot) to accelerate data engineering; comfortable as a visible thought-leader on AI practices for a small team
• DevOps: Experience integrating pipelines with CI/CD, version control, branching strategies (dev → test → prod), DACPAC or equivalent schema-migration tooling, and managed-identity-based deployment
• Communication: Able to translate infrastructure decisions and engineering workflows into business impact for non-technical stakeholders

• ~40,000 attributed patients across MSSP, ACO REACH, GUIDE, and LEAD
  • Various alignment, benchmark, and claim files spanning CMS/CMMI programs across multiple ACOs
• Three distinct Medicare claim feeds (DPC, CCLF, BCDA), each with its unique schema, inconsistencies, and challenges
• Internal clinical/operational data systems and structures
• External vendor data feeds, with planned data source expansion as Ennoble Care’s ACO portfolio grows
• Existing data engineering foundation to continue building upon

Ennoble Care is an Equal Opportunity Employer, committed to hiring the best team possible, and does not discriminate against protected characteristics including but not limited to - race, age, sexual orientation, gender identity and expression, national origin, religion, disability, and veteran status.