Lead QA Automation Engineer

Reinsurance Group of America, Incorporated

Lead QA Automation Engineer designing and implementing scalable test automation frameworks for enterprise data products at RGA. Collaborating with product and engineering teams to ensure high-quality data solutions.

Posted 7/30/2026full-timeRemote • Illinois • 🇺🇸 United StatesSenior💰 $107,060 - $159,390 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading QA initiatives, developing test automation frameworks, and ensuring data quality across big data platforms. Proficient in data validation techniques, CI/CD integration, and mentoring QA teams to drive continuous improvement in testing processes.

Highest-signal resume keywords

Big Data ExperienceData Testing ExpertiseSQL ProficiencyTest Automation FrameworksData Quality Validation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisETL TestingData Pipeline ValidationData Lake ValidationData Completeness ChecksCI/CD Pipeline UnderstandingAPI TestingPerformance TestingData Security KnowledgeTest Metrics Implementation

Soft Skills

Problem-SolvingAnalytical SkillsTeam LeadershipCommunication Skills

Tools & Technologies

PlaywrightSeleniumCypressHiveSparkNoSQLAzureAWSSnowflakeDatabricks

Industry Keywords

Data QualityData ValidationData IngestionData ModelingData ProcessingData ObservabilityQuality MetricsKPI MonitoringCompliance ValidationData Warehouse Testing

Tech Stack

Tools & technologies

AWSAzureCloudCypressETLNoSQLSeleniumSparkSQL

About the role

Key responsibilities & impact

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

What you’ll need

Bachelor’s Degree in Arts/Sciences (BA/BS) or equivalent education/ experience - Required
8+ years big data or relevant experience - Required
8+ years experience with cataloging, modeling, ingestion, processing, and streaming technologies and processes - Required
4+ years of Data Analysis experience - Required
Demonstrated ability to lead QA teams, drive automation strategy, and influence cross-functional stakeholders - Required
Strong problem-solving and analytical skills with ability to validate complex data scenarios and communicate insights clearly - Required
Expertise in data testing (ETL, data pipelines, data lake validation, reconciliation) - Required
Proficiency in SQL and data validation techniques (data completeness, accuracy, lineage checks) - Required
Strong understanding of CI/CD pipelines and automation integration - Required
Experience validating data quality rules, transformations, and business logic across data layers - Required
Knowledge of data security, privacy (PII), and compliance validation - Required
Experience with API and integration testing (REST, JSON, data contracts) - Preferred
Hands-on experience with test automation frameworks (Playwright, Selenium, Cypress) for UI + data validation - Preferred
Experience working with big data platforms (Hive, Spark, NoSQL, data lake architectures) - Preferred
Experience with data warehouse / BI testing (report validation, dashboards, metrics reconciliation) - Preferred
Familiarity with cloud data platforms (Azure, AWS, Snowflake, Databricks) - Preferred
Exposure to data observability, monitoring, and quality frameworks - Preferred
Experience implementing test metrics, KPIs, and quality dashboards - Preferred
Knowledge of performance testing for data pipelines - Preferred

Benefits

Comp & perks

annual bonus plan
participation in long-term equity incentive plan
full range of health benefits
retirement benefits