Healthcare Data Engineer

Habitat Health•San Francisco, CA

10h

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.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, Statistics, or related technical field.
Experience with data engineering concepts through internships or 3+ years in a related technical role.
Familiarity with at least one cloud platform (Azure preferred) and a willingness to learn cloud‑based data tools and services.
Understanding of data architecture principles and interest in learning how to design scalable, secure, and cost‑efficient systems.
Exposure to building or maintaining data pipelines using tools like Airflow or Prefect
Ability to work with structured and unstructured data sources, including files, APIs, and common data transfer methods.
Solid foundational Python and SQL skills, with the ability to write clean, maintainable code and eagerness to grow into more advanced development.
Ability to leverage (not rely on) AI coding tools like Claude Code/Github Copilot/Cursor
Awareness of data governance, access controls, and security best practices.
Comfortable working independently on well‑defined tasks.
Alignment with our mission and values, and enthusiasm for contributing positively to the team’s culture and daily practices.

Nice To Haves

Hands-on healthcare data experience (claims, EHR, FHIR)
Awareness of the Tuva open-source healthcare data model and dbt pipelines

Responsibilities

Support the development and maintenance of secure, scalable data systems that enable clinical, operational, and financial analytics in a HIPAA‑regulated environment.
Contribute to building and operating data pipelines that ingest, transform, and standardize data from internal and external healthcare sources such as EHRs, claims vendors, and SDOH APIs.
Work closely with analysts and business stakeholders to understand requirements and help create reliable, analytics‑ready datasets and basic data models.
Assist in documenting data processes and governance practices, including data lineage, access controls, and handling procedures for sensitive health information.
Participate in data quality efforts by implementing validation checks, monitoring data flows, and helping identify anomalies that could impact downstream analytics.
Help develop and maintain reusable dbt models and shared data transformations, with exposure to open healthcare data models like Tuva, OMOP, or FHIR.
Collaborate with senior engineers to improve infrastructure and team processes, taking on increasing responsibility as skills grow and the data engineering function expands.