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AI Data Pipeline Unit Test Generator

Benjamin Leclerc

Contract · Job · Denver

About the role

Airflow DAGs, Docker containers, and dozens of streaming pipelines with almost no automated test coverage are what you'll be working against. If writing tests that catch pipeline bugs before production sounds satisfying, this role is for you. You will build a tool that automatically generates unit tests for new Airflow DAGs based on schema and transformation metadata, reducing the manual test-writing burden on our data engineering team. You'll join a cross-functional squad with defined sprints and a weekly sync with the pipeline reliability lead. This is interesting because almost nobody has solved automated test generation well for data pipelines specifically, so there's real room to build something genuinely useful here.

Responsibilities

  • Build automated unit test generation for Airflow DAGs
  • Use schema and transformation metadata to generate test cases
  • Reduce manual test-writing burden on the data team
  • Work hybrid with the pipeline reliability lead
  • Maintain generated test coverage metrics

Requirements

  • 1-2 years of experience with data pipelines or testing tools
  • Familiarity with Airflow and Docker
  • Basic Python skills
  • Interest in developer tooling for data engineering

Benefits

  • Hybrid schedule with flexible in-office days
  • Contract with potential conversion to full-time
  • Mentorship from senior data engineers
  • Home office stipend

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Job Type

Contract

Level

Junior

Language

English

Salary Range

$80k – $100k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python airflow docker

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