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Senior QA Lead – Master Data Management
We are seeking a highly motivated and experienced Senior QA Lead to join our Master Data Management (MDM) team. In this role, you will lead the quality assurance strategy and execution for cloud-native data platforms and pipelines built on AWS. Our systems rely heavily on Python, data integrity, and pipeline automation, with a strong focus on scalability and reliability.
As QA Lead, you will collaborate with data engineers, DevOps, and product teams to validate complex data workflows and ensure adherence to the highest standards of data quality, governance, and system performance.
Key Responsibilities
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Lead end-to-end QA efforts for cloud-based data engineering solutions on AWS.
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Design, build, and maintain automated testing frameworks in Python to validate ETL pipelines, APIs, and batch processes.
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Develop robust data validation processes to ensure accuracy, completeness, and consistency across systems such as S3, Redshift, Glue, and Snowflake.
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Partner with data engineering teams to define and execute test strategies for data transformations and workflows.
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Implement governance and quality checks for MDM systems to ensure consistency in reference data.
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Integrate automated testing into CI/CD pipelines using tools like Jenkins, GitHub Actions, or AWS CodePipeline.
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Define and monitor QA metrics including test coverage, defect rates, and data quality KPIs.
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Perform regression, integration, performance, and exploratory testing across various data platforms.
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Review data pipelines, code, and infrastructure for potential quality and performance issues.
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Ensure QA practices comply with data privacy, security, and governance standards.
Required Qualifications
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Bachelor’s degree in Computer Science, Engineering, or a related field.
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5+ years of QA experience, with at least 2 years in a senior or lead role.
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Strong Python skills and experience with testing frameworks like PyTest
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Proven expertise in testing data engineering workflows, including ETL/ELT processes.
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Hands-on experience with AWS services such as S3, Lambda, Glue, Redshift, Athena, and CloudWatch.
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Strong understanding of SQL, data modeling, and database validation techniques.
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In-depth knowledge of QA methodologies for distributed data systems.
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Familiarity with MDM practices, including reference data validation and governance.
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Experience working with CI/CD tools in a cloud-native environment.