Summary
We are looking for a Staff QA Automation Manager to lead QA operations for a suite of internal back-office web applications and the Databricks data platform that powers them. In this hands-on leadership role, you will set QA strategy and standards, mentor a team of onshore and nearshore testers, and contribute directly to testing and automation. A primary focus will be data quality: designing and automating validation across Databricks notebooks, pipelines, and Power BI reports, and remediating existing data quality gaps across prioritized datasets. Operating with a high degree of autonomy in an agile environment, you will partner closely with developers, data teams, and business stakeholders to bring structure, capacity planning, and clear release visibility to the QA function. Please note: this role is strictly onshore (US-based).
Professional Experience
- Must be physically located in and authorized to work in the United States
- 8+ years of QA experience, including 3+ years in a hands-on QA Lead or QA Manager role
- Proven experience mentoring and growing QA teams, including work planning, prioritization, and hiring
- Strong experience in manual and automated API, UI, and database testing
- Hands-on experience in data validation and ETL/ELT pipeline testing, including SQL-based reconciliation and data quality checks
- Experience testing in cloud environments (Azure preferred) within agile teams
Key Responsibilities
- Lead, mentor, and develop a team of onshore and nearshore QA testers, owning work planning, prioritization, and capacity allocation
- Define and implement QA strategy, processes, and best practices across new and existing systems
- Test, automate, and document internal back-office web applications hosted in Azure, along with their supporting Databricks notebooks
- Test and validate Databricks notebooks, jobs, and pipelines, including data transformations, data quality automations, and pipeline-based tests
- Design and automate data validation across Databricks, covering source-to-target reconciliation, Unity Catalog, Databricks dashboards, and verification of Power BI figures against underlying data
- Lead the remediation of data quality issues across prioritized datasets
- Ensure web applications and Power BI reports function correctly across desktop and mobile browsers
- Review test code, enforce automation coding standards, and optimize new and existing test suites
- Investigate application performance issues and coordinate optimization efforts with development
- Partner with business users to understand their processes and propose technical and non-technical solutions
- Track and report on quality metrics, test coverage, and release readiness
Required Technical Skills
- Strong hands-on experience in the following areas:
- Test Automation: Python, Pytest, Playwright for UI automation, API testing with Requests (Swagger/OpenAPI)
- Data Platform: Databricks (Notebooks, Jobs, Pipelines, Unity Catalog, Dashboards)
- Data Quality & Validation: Source-to-target reconciliation, data transformation testing, ETL/ELT pipeline testing, automated data quality checks
- Databases & SQL: Advanced SQL for reconciliation and backend validation; Spark SQL
- Cloud: Azure
- QA Management: Test management tools (Qase preferred), quality metrics, coverage, and release readiness reporting
Nice to Have
- Experience with the Databricks Data Quality framework, Databricks Asset Bundles, and ELT/transformation testing frameworks
- Experience testing or validating Power BI reports
- Experience with CI/CD pipelines (GitHub Actions or Azure DevOps)
- Experience with performance testing tools
- Experience managing distributed or nearshore teams
- Familiarity with AI-assisted testing and development tools such as Claude Code
