Data Engineer

About the role

This is a Data Platform Engineer opportunity with a growing Series B New York health tech business that uses AI orchestration to improve revenue cycle management for healthcare providers. It is a growth role building and operating the pipelines that bring customer EHR data into Snowflake, plus the models that turn raw data into core business entities. Work is scoped with senior engineers, so the role suits someone who wants to learn a complex domain quickly. You’ll build and maintain pipeline components within larger workstreams, write production Python and SQL for extracts, transformations and data quality checks, and contribute to core entity models while learning the revenue cycle domain. You’ll debug data quality and pipeline issues to root cause and join the on-call rotation with senior support. The stack includes Snowflake, SQLMesh, Temporal, Python, AWS and Datadog. The ideal candidate will have 2+ years of software or data engineering experience with production code, solid Python and SQL fundamentals, and exposure to at least one part of the modern data stack such as a warehouse, orchestrator or transformation framework. Deep warehouse experience and healthcare domain knowledge are not required. Strong debugging instincts, openness to feedback and an interest in healthcare data matter more. This is a hybrid position in New York City, suited to an early-career data engineer looking for fast progression. 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