Sr. Healthcare Data Engineer

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 looking for someone who can: 

• Design, implement, and maintain scalable, HIPAA-compliant data architecture to support clinical, operational, and financial analytics. 

• Build and manage robust data pipelines to ingest, transform, and standardize data from internal and external healthcare sources (e.g., EHRs, claims vendors, SDOH APIs). 

• Collaborate closely with analysts and business users to translate requirements into performant data models and analytic-ready datasets. 

• Establish and document data governance standards, including lineage, access control, and auditing protocols for sensitive health information. 

• Lead data quality initiatives including validation rules, monitoring, and anomaly detection to ensure trust in downstream analytics. 

• Prototype and productionize reusable dbt models and libraries aligned to open healthcare data models (e.g., Tuva, OMOP, FHIR). 

• Serve as the technical lead for growing a high-functioning data engineering team and scaling infrastructure to meet business needs. 

Qualifications:  

• At least 5 years of data engineering experience  

• Strong proficiency with a modern cloud-based data stack, preferably Azure Data Services 

• Ability to design and implement scalable, cost-efficient, HIPAA-compliant data architecture 

• Experience building end-to-end production grade data pipelines soup to nuts (e.g. Airflow, Databricks, Azure Data Factor)  

• Experience ingesting external data files and APIs (OneDrive, SFTP, claims vendors, etc.) 

• Expert-level Python and SQL coding skills  

• Can design and develop both normalized and analytic schemas for downstream analytics 

• “Analyst as customer” mentality; experience enabling analytic use cases via dbt or similar tools 

• A willingness to crank through the less glamorous aspects of building data products that delight (e.g. data cleaning, quality checks, source to target mapping, documentation, etc.) 

• Help set up and enforce data governance, access controls, encryption, and auditing 

• The ability to “do it all yourself” at first, and build a data engineering team over time 

• Aligns with our purpose and our values, and is excited about living those out in daily practice  

• Ability to lead with influence [especially for cross-functional roles] 

 

 

Nice to have: 

• At least 3 years of hands-on healthcare data experience (claims, EHR, FHIR) 

• Knowledge of the Tuva open-source healthcare data model and dbt pipelines 

• Management experience (people management, work throughput and quality control) 

• Medical claims expertise (UB-04, HCF