Staff Software Engineer - Data Platform & Integrations (Remote)

Astrana Health, Inc.

Phoenix (AZ)

On-site

USD 150,000 - 230,000

Full time

10 days ago

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Job summary

Astrana Health is seeking a Staff Software Engineer to own a cross-cutting technical domain—data platform, integration layer, or clinical data model. This hands-on role emphasizes building high-quality systems and guiding other engineers.

You will set architecture, defend design choices, manage data models for eligibility, claims, and quality data, and drive reliability across the stack. This US-based remote role prefers candidates near the Los Angeles area.

Qualifications

8+ years of professional software engineering experience.
Four-year undergraduate degree in CS, Math, Physics, or Engineering.
Full-stack experience owning systems from the data layer through the API to the UI.
Strong TypeScript and SQL with data modeling experience.
Data and analytics savvy; able to assess report plausibility.
Production experience with React.
Docker and container-based deployment.
Hands-on cloud infrastructure ownership (Azure, AWS, or GCP).
Experience with AI development tools for coding agents and assistants.

Responsibilities

Set technical direction for your domain: what we build on, what we migrate off, and what we deliberately tolerate.
Make and defend architecture and infrastructure choices on cost, operational burden, hiring implications, and exit cost as well as capability.
Build the hard core of new systems yourself, and the reference implementations and tooling that let other engineers move fast inside them.
Evolve existing systems: decomposition, strangler patterns, deprecations, and migrations off old paths that actually finish.
Design for our failure domains. Know what happens when a partner feed dies, a vendor deprecates an API, or a region goes down, and what the recovery path is.
Own the shape of our data. Decide how eligibility, claims, clinical, and quality data are modeled, joined, and served for both product features and analytics, and make it easy for engineers and analysts to get trustworthy answers out of it.
Set cross-cutting standards (schema conventions, service templates, CI/CD, environment and test-data strategy) and get them adopted.
Turn recurring classes of incidents into structural fixes.
Manage technical debt as a portfolio: what we carry, what it costs us, and what we pay down next.
Grow the senior bench: run technical interviews, calibrate hiring and promotion decisions, and develop senior engineers so more of them operate at a staff level.
Say the unpopular thing, early and clearly, to engineering and non-engineering leadership alike.