Data Engineer with Strong Testing

About

You will own the exploratory, production-oriented quality assurance for customer-critical integration paths within a modern data stack environment.

Responsibilities

• Execute exploratory QA on integration paths across DBT, Airflow, Terraform, ADF, and GitHub Actions.
• Recreate and document integration issues surfaced by customers and support teams.
• Test and validate APIs, CLI behavior, and system functionality under varied configurations.
• Partner with Support and Product to prioritize edge case testing based on real-world impact.
• File actionable, reproduction-ready bugs with detailed context for the engineering team.

Requirements

• 3+ years experience in software QA, support engineering, or technical testing roles.
• Familiarity with modern data engineering platforms: Airflow, Terraform, DBT, Databricks, GitHub Actions, Azure Data Factory.
• Experience manually setting up test environments to reproduce cross-system issues.
• Proficiency in testing APIs and CLI tools to validate system integrations.
• Strong written skills for defect documentation and QA communication.
• Self-starter mindset capable of exploring unfamiliar systems and proposing next steps.
• Experience working in complex, high-variance customer environments.
• Familiarity with AWS, Snowflake, and Azure.
• Knowledge of Python.