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're ~25 people. >$32M raised. SF-based, hybrid-friendly. And, we're delivering results that are changing lives.
Senior Data EngineerHealthLeap 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.
Intro call
Data pipeline design
Practical data exercise
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.
Skills Required
- 5+ years building production data systems
- Strong Python and SQL skills
- Experience owning pipelines dependent on messy, changing external data
- Strong data modeling skills and judgment regarding correctness, monitoring, and recovery
- Ability to trace problems across systems and own fixes through production
- Experience building data pipelines for machine learning products
- Experience with clinical data, EHRs, HL7, or FHIR
- Early-stage experience building and operating core data systems
What We Do
HealthLeap is an AI-driven clinical decision support platform designed to improve patient outcomes and hospital margins. It serves as an AI screening 'safety net' for hospitalized patients, primarily focusing on daily malnutrition screening to identify high-risk inpatients earlier than manual tools. By surfacing patients who need care, it enables timely clinician intervention, reduces hospital readmission rates, and improves billing accuracy for hospitals.
