Lead QA Engineer
Hariharan SUnited StatesLEADPosted 10d ago
COBOLJCLDB2 for z/OSIMS DBIMS DCVSAMCICSTSO/ISPF3270 emulatorsCA-7Control-MPythonpytestpandasGoAWSS3LambdaRDS/AuroraAWS DMSCloudWatchSQLPostgreSQLGitJiraCI/CD pipelinesGitHub CopilotClaude CodeCursor
About the Role
We are looking for an experienced Lead QA Engineer with strong hands-on mainframe testing expertise to support a mainframe-to-AWS modernization initiative. The ideal candidate will have experience validating legacy mainframe applications, building automated testing frameworks, and ensuring functional and data equivalence between legacy and modernized cloud systems.
Key Responsibilities
• Develop and execute comprehensive test strategies for mainframe modernization projects
• Validate data migration from DB2, IMS, VSAM, and flat files to AWS-based platforms
• Perform parallel runs and compare legacy system outputs against modernized workloads
• Build automated testing and reconciliation frameworks using Python and Go
• Validate batch processing, job dependencies, restart and recovery behavior, and system performance
• Use AI-assisted tools to accelerate test case generation, legacy code analysis, and defect investigation while ensuring accuracy and data security
• Support performance testing, rollback rehearsals, cutover validation, and release sign-off
Requirements
• 8–10 years of experience in mainframe testing
• Strong hands-on mainframe testing experience with COBOL, JCL, DB2 for z/OS, IMS DB, IMS DC, VSAM, and CICS
• Ability to analyze COBOL programs, JCL job streams, copybooks, and legacy business logic to develop comprehensive test scenarios
• Experience with TSO/ISPF, 3270 emulators, and batch scheduling tools such as CA-7 or Control-M
• Strong Python automation skills using pytest, pandas, and related testing libraries
• Working proficiency in Go for data reconciliation, validation utilities, and high-volume testing
• Hands-on experience with AWS services, including S3, Lambda, RDS/Aurora, AWS DMS, and CloudWatch
• Experience with parallel testing, batch equivalence validation, data migration testing, regression testing, and cutover readiness
• Practical experience using AI-assisted development and testing tools such as GitHub Copilot, Claude Code, Cursor, or similar tools
• Experience with SQL, PostgreSQL, Git, Jira, and CI/CD pipelines