Engineering Manager

About the role

This is an Engineering Manager (Data Platform) 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 player-coach role leading a team of four to six data platform engineers, owning the team’s roadmap, delivery and health while staying technically hands-on in a lean environment. You’ll manage engineers through performance, growth and coaching, own the team roadmap with Product and the Head of Data, and set architecture direction with senior engineers. You’ll own hiring, run production reliability, SLAs, on-call health and warehouse cost, and partner with data science, forward-deployed engineering and customer-facing teams. You’ll also build lean processes and drive AI-native engineering practice. The stack includes Snowflake, SQLMesh, Temporal, Python, AWS, Fivetran and Datadog. The ideal candidate will have 8+ years in data or backend engineering, including 2+ years managing engineers, and can still code well enough to pass a coding screen and discuss warehouse, orchestration and pipeline failure design. Production experience with Snowflake or similar, Temporal or Airflow and SQLMesh or dbt is expected, along with evidence of hiring and scaling a team. This is a hybrid position in New York City, suited to a manager who wants to stay close to the code at startup pace. 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