Staff Data Engineer

About the role

This is a Staff Data Engineer opportunity with a Series A US healthtech business whose AI platform gives hospitals end-to-end visibility into their supply chain. The role sets technical direction for the data platform on AWS, covering ingestion, transformation, storage and serving, and works with sensitive hospital operational data. You’ll build batch and near-real-time pipelines with SLAs and observability, model supply chain data from external hospital ERP systems into a reusable warehouse, and migrate legacy assets into it. You’ll tune performance and cost across Postgres and Snowflake, set data engineering standards, partner with analytics and product teams on durable data models, and lead governance for sensitive data including lineage, access, retention, auditability and de-identification. The ideal candidate will have 8+ years in data or software engineering, including end-to-end ownership of production systems. Expert SQL (including query plan analysis), strong Python, deep experience with Postgres and Snowflake, hands-on orchestration experience (Airflow, Dagster, Prefect, dbt, Fivetran, Spark or Kafka) and production AWS experience are expected, along with a record of leading multi-quarter, cross-team initiatives. Healthcare data (claims, EHR, HL7/FHIR) and ERP data experience would be advantageous. This is a fully remote US position. We're looking for someone curious, pragmatic, and eager to work across the stack with a small senior team. You'll own end-to-end delivery of major features, influence architecture, and mentor engineers.

What you'll do

• Ship customer-facing features on a weekly cadence.
• Partner with design and product on scoping and trade-offs.
• Drive technical quality through review, testing, and docs.
• Mentor one or two engineers on your team.

Requirements