Data Platform Engineer

Adonis•New York, NY

4d•Onsite

About The Position

The Data Platform Engineer will build and operate components of our data platform, including pipelines that move healthcare data from customer EHR systems into Snowflake, and models that transform raw data into trusted core entities. This role involves working within workstreams architected by senior engineers, owning components end-to-end from building and testing to production operation and maintenance. It is a growth-oriented position offering direct exposure to enterprise-scale healthcare data challenges, a modern technology stack (Snowflake, SQLMesh, Temporal, Python, AWS, Datadog), and mentorship from senior engineers. The expectation is for rapid development, starting with components and progressing to owning workstreams.

Requirements

2+ years of software or data engineering experience with production code.
Solid Python and SQL fundamentals.
Understanding of how data moves through a system.
Exposure to at least one part of the modern data stack: a cloud warehouse, an orchestration tool, or a transformation framework.
Strong debugging instincts and honesty about knowledge gaps.
Ability to respond well to feedback and demonstrate a clear trajectory for growth.
Interest in healthcare data, with an appetite for a messy, regulated domain.

Nice To Haves

Snowflake, SQLMesh/dbt, Temporal, or AWS exposure.
Prior contact with healthcare, claims, or other regulated data domains.

Responsibilities

Build and maintain pipeline components within larger workstreams, with architecture guidance from senior engineers.
Write production Python and SQL code, including extract logic, transformations, and data quality checks.
Contribute to core entity models and learn the RCM domain that drives them.
Debug data quality and pipeline issues to root cause.
Run the components they build and participate in the on-call rotation with support from senior engineers.
Develop AI-natively, utilizing AI coding tools for design, build, and review processes.