QA Manager – Data Warehouse Testing

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee QA initiatives within the Data Warehouse team, guaranteeing the accuracy, integrity, reliability, and consistency of enterprise data.

• Create and implement testing strategies for data warehouses, ETL/ELT processes, Databricks notebooks, data pipelines, and transformations.

• Design and automate frameworks for data validation, including source-to-target reconciliation, data quality assessments, and transformation testing.

• Verify Databricks jobs, pipelines, Unity Catalog components, and related data workflows.

• Utilize SQL and Python to build automated testing solutions, detect data discrepancies, and resolve data quality challenges.

• Validate reporting and analytics downstream, including reconciling Power BI reports with their underlying data sources.

• Establish and enhance QA processes, testing standards, automation frameworks, and best practices.

• Lead, mentor, and manage a small team of nearshore QA engineers, overseeing task allocation, priorities, deliverables, and performance evaluations.

• Assess the QA landscape, identify testing deficiencies, and implement improvements for quality and efficiency.

• Evaluate team capacity and resource needs, including creating business cases for additional headcount.

• Define and track QA metrics, test coverage, defect trends, and readiness for release.

• Collaborate with data engineers, developers, and business stakeholders to align QA practices with organizational requirements.

• Write, review, and maintain automated tests using Python, Pytest, and SQL.

• Conduct API, database, and web application testing.

• Assist with UI automation using Playwright.

• Review automation code, set coding standards, and optimize testing suites.

• Integrate testing into development and deployment workflows, including CI/CD pipelines.

• Assess and embrace emerging QA technologies and AI-assisted development tools, such as Claude Code.

⛳️ Requirements

• Over 8 years of experience in Quality Assurance, with a minimum of 3 years in a hands-on QA Lead or QA Manager role.

• Extensive experience in data warehouse testing, ETL/ELT testing, data validation, and quality assurance for data.

• Demonstrated ability to establish QA strategies, implement processes, and enhance or build QA functions.

• Experience in managing and mentoring QA engineers, preferably including distributed, offshore, or nearshore resources.

• Strong hands-on experience with SQL, focusing on data reconciliation, transformation validation, and data quality testing.

• Proficient in Python and Pytest for automation of testing processes.

• Background in developing and maintaining automated testing frameworks.

• Familiarity with API, database, and web application testing.

• Experience using Playwright for UI automation.

• Proven experience in testing data pipelines and applications within cloud environments.

• Solid understanding of Agile development methodologies and QA best practices.

• Ability to balance strategic leadership roles with hands-on technical contributions.

• Exceptional communication, stakeholder management, and organizational capabilities.

• Capacity to identify resource needs, communicate technical challenges, and suggest improvements to leadership.

• Eagerness to learn and adopt new technologies and AI-assisted development tools.

• Preferred: hands-on experience testing Databricks environments, including notebooks, jobs, pipelines, and Unity Catalog.

• Preferred: experience with Azure cloud services and contemporary cloud-based data platforms.

• Preferred: familiarity with Spark SQL and Databricks data quality and automated testing frameworks.

• Preferred: experience in validating Power BI reports and analytics data.

• Preferred: knowledge of CI/CD tools such as GitHub Actions or Azure DevOps.

• Preferred: familiarity with test management tools like Qase.

• Preferred: experience in performance testing and troubleshooting.

• Preferred: background in establishing QA teams or testing functions from inception.

• Preferred: experience with AI-assisted development tools such as Claude Code.

• Financial services experience is advantageous but not mandatory.

🏝️ Benefits

• Opportunity for remote work.

• East Coast working hours.

• Contract position.