Job description

We have partnered with a client of ours here in Austin, Texas who is looking for a talented Test Engineering Manager – Data Platforms to join their team! Seeking a driven and hands-on Test Engineering Manager to lead the charge in shaping our clients quality engineering efforts within our dynamic data engineering group. If you’re passionate about building robust systems, leading talented teams, and diving deep into data-centric technologies, this is your opportunity to make an impact. You’ll guide a team that ensures the reliability and accuracy of our data pipelines, integrations, and platforms — the backbone of our decision-making ecosystem. What You’ll Be Doing • Lead and Empower: Build, mentor, and lead a high-performing team of test engineers, helping them grow technically and professionally. • Set the Strategy: Design and implement comprehensive testing strategies across large-scale data projects — from data lake migrations to API integrations. • Champion Data Quality: Collaborate with engineers, analysts, and stakeholders to ensure the integrity and performance of our data workflows. • Build the Tools: Develop and maintain testing frameworks and validation tools using Python (Pandas, PySpark, or Polars) and SQL. • Automate Everything: Create and manage test automation suites for both data validation and front-end regression testing using tools like Cypress, Selenium, or Playwright. • Own the Process: Drive best practices in quality assurance, automation, and CI/CD across the engineering lifecycle. • Test at Scale: Manage automated testing of complex systems including Azure Data Factory, Snowflake, SSIS packages, and REST APIs. What You Bring to the Table • Proven leadership experience managing QA or test engineering teams — ideally in data-heavy environments. • Strong hands-on coding abilities in Python, especially for test automation and data validation. • Solid SQL expertise and a deep understanding of relational databases like SQL Server. • Experience with Snowflake, Azure Data Factory, and other cloud data services. • Familiarity with Databricks, Jupyter Notebooks, or similar environments is a plus. • Practical experience with testing ETL processes (SSIS packages, data pipelines). • Comfortable working with API testing and front-end automation tools (e.g., Playwright, Selenium). • A collaborative spirit and a passion for mentoring and knowledge sharing. • Experience embedding test strategies within CI/CD workflows. • Bonus: Exposure to cloud-native architecture patterns and modern data platform design.

Requirements