Principle Data Analyst

Habitat Health

2h•$146,000 - $170,000

About The Position

At Habitat Health, we envision a world where older adults experience an independent and joyful aging journey in the comfort of their homes, enabled by access to comprehensive health care. Habitat Health provides personalized, coordinated clinical and social care as well as health plan coverage through the Program of All-Inclusive Care for the Elderly (“PACE”) in collaboration with our leading healthcare partners, including Kaiser Permanente. Habitat Health offers a fully integrated experience that brings more good days and a sense of belonging to participants and their caregivers. We build engaged, fulfilled care teams to deliver personalized care in our centers and in the home. And we support our partners with scalable solutions to meet the health care needs and costs of aging populations. Habitat Health is growing, and we’re looking for new team members who wish to join our mission of redefining aging in place. To learn more, visit https://www.habitathealth.com. Role Scope: We are seeking a Principal Data Analyst to serve as a technical and analytical leader across our healthcare data ecosystem. This role goes far beyond report building - you will define analytic standards, design core data models, and own the clinical and financial logic that leadership relies on to run the business working across Epic Clarity, medical claims, pharmacy claims, and other core data assets. This is a hands-on, senior-level individual contributor role for someone who combines deep Epic expertise with strong healthcare domain knowledge and modern analytics / engineering practices.

Requirements

10+ years of hands-on experience as an analyst / leader in healthcare data analytics
Expert level mastery of Epic Clarity and/or medical claims datasets
Advanced SQL skills, including complex joins, window functions, performance optimization, and readable, maintainable query design
Experience designing and building enterprise-grade dashboards with drill-down functionality in Power-BI or another data visualization tool
Deep understanding of healthcare data ontologies including CPT, HCPCS, HCC, ICD-10, NDC, Revenue Codes, Type of Bill, LOINC, UB/HCFA claims, etc.
Proven experience developing longitudinal patient analyses using complex clinical logic, while interfacing with subject matter experts like MDs, Pharm-Ds, epidemiologists, etc.
Excellent communication skills; able to explain technical concepts to non-technical stakeholders at a high level with all the supporting documentation in your back pocket
Track record of working in cross-functional teams, ideally in a value-based care, PACE, or managed care environment
A team first mentality within our team; a company first mentality when working across Habitat teams

Nice To Haves

Experience developing in a modern data stack using Databricks, Python, and/or Airflow
Experience working in early-stage or rapidly scaling healthcare organizations
Experience with Medicare Advantage, PACE, and / or dual eligible populations

Responsibilities

Master enterprise-level analytics across Habitat’s Epic Clarity, medical claims, pharmacy claims, and related healthcare and operational data assets
Translate complex clinical and financial questions into durable, scalable analytic solutions that are designed and developed with a “platform-first mentality” to enable other developers
Support executive and clinical leadership decision-making by designing, building, and maintaining trusted dashboards, KPI definitions, and “curated” analytic DataMarts
Use SQL, Power BI, Git, and Jira in a manner that raises the bar and sets the standards for best practices within the broader data team
Partner with data engineering to design and govern canonical data marts, ETL processes, and documented business rules that ensure consistency across all downstream analytics
Develop and maintain rigorous clinical and claims-based logic for longitudinal patient analyses, quality measures, utilization metrics, and value-based care performance
Lead data quality, testing, documentation, and code review standards to ensure analytics are accurate, auditable, reproducible, and production-ready
Build and maintain externally facing regulatory and audit reporting (CMS, Medicaid, PACE) in a scalable and defensible manner
Act as a technical leader and mentor within the data team, elevating analytic rigor and best practices without formal people management