Senior Data Engineer

Every day, millions of hospitalized patients who need intervention are missed because clinicians simply can't see everything. Healthleap is building the AI operating system that helps care teams identify these missed patients, enabling them to improve health outcomes and generate millions of dollars. Healthleap is changing what is possible: closing gaps that traditional workflows and clinician capacity could never.

Over the past year, we've grown contracted revenue more than 13x, expanded rapidly across leading health systems, and now help care teams identify patients across millions of inpatient encounters.

We've raised $38M, backed by Sequoia, First Round and Hummingbird. SF-based and in person. And we're delivering results that are changing lives.

HealthLeap runs on data. We’re live at 40+ hospitals and plan to add another 100. You’ll build the core pipelines that move messy clinical data from hospital systems into model inputs, analytics, and the APIs behind what clinicians see.

You’ll make that data usable and reliable. When a feed arrives late, a field changes, or a number looks wrong, you’ll trace it through the system and fix the cause.

• Build and operate pipelines from hospital ingestion through transformation and delivery.

• Produce trusted data for ML pipelines, customer analytics, and user-facing APIs.

• Define data contracts and checks that catch missing records, schema changes, and incorrect values.

• Handle backfills, late data, failures, and recovery.

• Work with integration, ML, and product engineers to get data reliably where it needs to go.

• 5+ years building production data systems, with strong Python and SQL.

• Experience owning pipelines that depend on messy, changing external data.

• Strong data modeling and judgment about correctness, monitoring, and recovery.

• The ability to trace a problem across systems and own the fix through production.

• Experience building data pipelines for ML products.

• Experience with clinical data, EHRs, HL7, or FHIR.

• Early-stage experience building and operating core data systems.

• You want to own one piece of the data stack. You’ll work across ingestion, model inputs, analytics, and product APIs.

• You want predictable 9-to-5 hours. We protect deep rest, but a hospital go-live can mean a 60+ hour week.

No LeetCode or puzzles. Use the tools you’d use on the job, including AI.

1. Intro call

2. Data pipeline design

3. Practical data exercise

4. Onsite with the team in San Francisco

We decide the same week as the onsite.

• $175,000–$275,000 base plus meaningful equity

• 100% covered healthcare premiums

• Unlimited PTO with a 20-day minimum

• 4% 401(k) match

• Laptop and home office budget

San Francisco, in person. We work together in the office by default, with flexibility to work from home when needed. We judge output, not hours.

If you're passionate about applying frontier AI to real-world impact, join us in building healthcare's future.