Lead QA Automation Engineer
United States of America
Full Time
3 hours ago
$107,000 - $159,000 USD
H1B Sponsor Likely
Key skills
QA AutomationTest Automation FrameworksData TestingETLData PipelinesData Lake ValidationData ModelingData IngestionData ProcessingData StreamingData AnalysisSQLData Validation TechniquesCI/CD PipelinesAutomation IntegrationData Quality Rules ValidationData Security ValidationData Privacy (PII) ValidationCompliance ValidationStakeholder ManagementNoSQLData LakeBISnowflakeDatabricksSparkCypressPlaywrightSeleniumIntegration TestingAWSAzureRepositoryCI/CDLeadershipMentoringTeam LeadershipCollaboration
About this role
Reinsurance Group of America is a purpose-driven organization focused on innovation and collaboration. The Lead QA Automation Engineer will drive quality engineering for enterprise data products, leading the design and implementation of scalable test automation frameworks and ensuring data quality across complex data pipelines and platforms.
Responsibilities:
- Lead small-to-medium QA initiatives with manageable risks, defining detailed test strategies, automation plans, and execution roadmaps
- Collaborate with business and IT stakeholders to translate data requirements into testable scenarios, ensuring data quality, validation, and completeness across the data lake
- Design, develop, and maintain test automation frameworks and quality engineering architecture aligned with big data platforms
- Perform data testing and validation, including data models, pipelines, transformations, and repository/catalog verification
- Build and support automated processes to validate data ingestion from source systems into the data lake, ensuring accuracy and reliability
- Provide team leadership, mentoring QA engineers, driving best practices, and owning overall quality outcomes for the team
- Develop test coverage models, data validation schematics, and capacity-aware testing strategies
- Drive continuous improvement in test automation efficiency, data validation performance, and security validation
- Establish and implement quality metrics, KPIs, and monitoring frameworks for data testing and automation effectiveness
- Recommend and enforce QA standards, automation frameworks, and testing processes across data platforms
Requirements:
- Bachelor's Degree in Arts/Sciences (BA/BS) or equivalent education/ experience
- 8+ years big data or relevant experience. Demonstrated ability to quickly learn new technologies
- 8+ years experience with cataloging, modeling, ingestion, processing, and streaming technologies and processes
- 4+ years of Data Analysis experience
- Demonstrated ability to lead QA teams, drive automation strategy, and influence cross-functional stakeholders
- Strong problem-solving and analytical skills with ability to validate complex data scenarios and communicate insights clearly
- Expertise in data testing (ETL, data pipelines, data lake validation, reconciliation)
- Proficiency in SQL and data validation techniques (data completeness, accuracy, lineage checks)
- Strong understanding of CI/CD pipelines and automation integration
- Experience validating data quality rules, transformations, and business logic across data layers
- Knowledge of data security, privacy (PII), and compliance validation
- Master's degree in Arts/Sciences (MA/MS)
- Experience with API and integration testing (REST, JSON, data contracts)
- Hands-on experience with test automation frameworks (Playwright, Selenium, Cypress) for UI + data validation
- Experience working with big data platforms (Hive, Spark, NoSQL, data lake architectures)
- Experience with data warehouse / BI testing (report validation, dashboards, metrics reconciliation)
- Familiarity with cloud data platforms (Azure, AWS, Snowflake, Databricks)
- Exposure to data observability, monitoring, and quality frameworks
- Experience implementing test metrics, KPIs, and quality dashboards
- Knowledge of performance testing for data pipelines