ashby
Data Platform Engineer
Adonis
New York City, USA
Full-time
Entry · 2+ years experience
Hybrid
USD 165000-190000 yearly / year
Discovered 1 weeks ago
SnowflakeSQLMeshTemporalPythonAWSDatadog
Free
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SnowflakeSQLMeshTemporal
Key Skills for This Role
SnowflakeSQLMeshTemporalPythonAWSDatadog
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The Role
You will build and operate components of our data platform: the pipelines that move healthcare data from customer EHR systems into Snowflake, and the models that turn that raw data into trusted core entities. You will work within workstreams scoped and architected with senior engineers on the team, and own your components end to end - building them, testing them, running them in production, and fixing them when they break.
This is a growth role. You will get direct exposure to enterprise-scale healthcare data problems, a modern stack (Snowflake, SQLMesh, Temporal, Python, AWS, Datadog), and senior engineers invested in ramping you. The expectation is a steep trajectory: components today, workstreams as you grow.
What You Will Do
- Build and maintain pipeline components within larger workstreams, with architecture guidance from senior engineers.
- Write production Python and SQL: extract logic, transformations, and data quality checks.
- Contribute to our core entity models and learn the RCM domain that drives them.
- Debug data quality and pipeline issues through to root cause, not just symptom.
- Run what you build. You join the on-call rotation with support from senior engineers.
- Develop AI-natively. AI coding tools (Claude Code and similar) are part of how this team designs, builds, and reviews.
What You Will Bring
2+ years of software or data engineering experience with production code you can walk through in detail.
Solid Python and SQL fundamentals. You may not have deep warehouse experience yet, but you understand 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 what you know versus what you are guessing.
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