Data Platform Engineer
Saragossa
About the role
About
Want to build AI data infrastructure that processes half a billion patient encounters a year?
An AI healthcare company — backed by one of the largest healthcare platforms in the U.S. — is hiring Data Platform Engineers at multiple levels (Mid to Staff) for its NYC-based team. This is startup-level ownership with enterprise-scale distribution: your systems will power production workflows across 95 of the top 100 U.S. health systems from day one.
The team is building an AI-native clinical and financial automation platform — agentic AI that reasons over full medical records, payer logic, and financial workflows to automate medical coding, billing, and follow-up. The data platform team owns the foundations that make this possible: the ingestion pipelines, backend schemas, and APIs that feed both the AI engine and the user-facing application. You won't just be building plumbing — you'll have full visibility into the business impact of what you ship, including the economic outcomes your work drives across the platform.
Tech Stack
- Python, Go, or Java
- Spark
- Kafka
- Airflow
- Terraform
- Docker
- Kubernetes
- FHIR/HL7 (bonus)
Qualifications
- At least 5 years of software engineering experience, with a minimum of 2 years building high-throughput data pipelines in production.
- Comfortable owning infrastructure end-to-end — Terraform, Docker, and Kubernetes are familiar territory.
- Hands-on experience with Spark, Airflow, or Kafka at real scale, and you understand what it takes to keep complex pipelines observable and reliable.
- Worked on the data backend of an ML system or a production SaaS application, and you know how to instrument systems so problems surface before users feel them.
- Come from a technically rigorous environment — whether that's a tier-one tech company, an AI lab, or a high-growth startup doing genuinely interesting work — and you can speak to both what you built and the business outcome it drove.
Compensation
- $180,000–$250,000 base (level dependent)
- Yearly bonus
- Long-term incentives
- Comprehensive benefits
Skills
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