Note: The job is a remote job and is open to candidates in USA. Falcon Smart IT seeks a Lead QA Engineer to validate a mainframe-to-AWS modernization program. The role owns testing strategy and execution for parallel runs, data migration, batch equivalence, automation, and cutover readiness, working with mainframe and cloud teams.
Responsibilities
- Define and own the test strategy, plans, and coverage for mainframe modernization workstreams (replatform and refactor), including functional, regression, integration, performance, and cutover testing
- Read and analyze COBOL, JCL, PL/I, and copybooks to derive test conditions, boundary cases, and expected results from business logic embedded in legacy code
- Execute and validate batch and online scenarios on z/OS, including JCL job streams, CICS and IMS DC transactions, and scheduler dependencies in CA-7 or Control-M
- Run parallel tests by feeding identical inputs to the legacy and modernized systems, diffing outputs at field level, and classifying each difference (defect, expected variance, rounding, or encoding)
- Validate data migration from DB2 z/OS, IMS DB, VSAM, and flat files to AWS targets (Aurora/PostgreSQL, DynamoDB, S3, Redshift), including row counts, checksums, field-level reconciliation, and COMP-3 to decimal precision and rounding checks
- Verify batch job equivalence: job sequence, return codes, restart and recovery behavior, and scheduling dependencies, including batch chains replaced by AWS Step Functions, SQS, SNS, and EventBridge
- Build and maintain automated test frameworks in Python (pytest, boto3, pandas) and use Go for high-throughput utilities such as large-file reconciliation and load generation
- Test APIs and new web front ends that replace 3270 screens, using requests/httpx, Postman/Newman, Pact, Playwright, or Selenium
- Plan and run performance, batch window comparison, failover, and rollback rehearsals ahead of each cutover
- Build test data by masking, subsetting, and generating synthetic data from production-like mainframe extracts, and confirm no unmasked PHI or member data reaches non-production AWS environments
- Integrate automated suites into CI/CD (GitHub Actions, Jenkins, AWS CodePipeline/CodeBuild) and provision repeatable test environments with Terraform or CloudFormation, Docker, and ECS/EKS
- Log, triage, and track defects in Jira, and publish results through Allure or pytest-html with clear evidence for release sign-off
- Follow change management, testing, and compliance practices appropriate for business-critical systems
- Mentor QA engineers on mainframe testing concepts and modernization test practices
Skills
- Bachelor's degree in computer science, Engineering, or a related field, or equivalent practical experience
- 8–10 years of software testing experience, including at least 4 years testing mainframe applications or mainframe data
- Ability to read COBOL and JCL, with working knowledge of PL/I, copybooks, and EBCDIC vs ASCII handling
- Hands-on experience with DB2 for z/OS (SQL, query validation), IMS DB (segments, hierarchical data), and IMS DC transactions
- Experience with VSAM and fixed-width flat files, including packed decimal (COMP-3) fields
- Experience with CICS, TSO/ISPF, 3270 emulators, and batch schedulers (CA-7 or Control-M)
- Strong Python test automation skills, with pytest as the primary framework and pandas for data comparison
- Working proficiency in Go for building supporting test and reconciliation utilities
- Working knowledge of core AWS services (S3, Lambda, RDS/Aurora, DMS, IAM, CloudWatch) sufficient to test mainframe workloads running on AWS
- Hands-on experience designing parallel run, data migration validation, and batch equivalence tests
- Strong SQL skills across DB2 and PostgreSQL
- Experience with Git, Jira, and CI/CD pipelines
- Strong written and verbal communication to bridge legacy mainframe teams and cloud engineering teams
- Practical use of AI coding and assistant tools (e.g., Claude Code, GitHub Copilot, Cursor, or similar) to accelerate COBOL/JCL comprehension, derive test conditions from legacy logic, and draft test cases and automation scripts
- Able to use AI tools to generate candidate test data scenarios, edge cases, and reconciliation checks, and to summarize defect patterns across parallel run results
- Able to critically review and validate AI-generated tests, code, and analysis for correctness before relying on them for release or cutover decisions
- Understanding of secure and compliant AI tool usage, including never entering PHI, member data, or other sensitive information from mainframe systems into prompts or external AI tools
- Able to identify where AI-driven automation can improve test coverage and modernization velocity, and champion adoption within the team
- Experience in the US health insurance or payer domain, particularly mainframe-based claims processing, eligibility, or core administration systems
- Exposure to healthcare data standards (X12 EDI, HL7, FHIR)
- Prior experience testing mainframe-to-cloud modernization or re-platforming initiatives
- Experience with AWS Mainframe Modernization, AWS Transform, or similar modernization tooling
- Familiarity with mainframe test and debugging tools such as File-AID, Abend-AID, or similar
- Relevant certifications: ISTQB, AWS Certified Cloud Practitioner, AWS Certified Solutions Architect, or IBM mainframe certifications
Benefits
- US (Remote)
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