Leads a cross-functional engineering team responsible for development, modernization, and support of mission-critical mainframe systems integrated with modern platforms (ZConnect, ZDIH) and enterprise DevOps tooling (GitLab CI/CD).
This role drives end-to-end ownership across architecture, engineering delivery, QA practices, and DevOps pipelines, ensuring scalable, secure, and high-quality solutions aligned with enterprise SDLC and regulatory standards.
Key Responsibilities
1. Technical Leadership & Delivery Ownership
- Lead design, development, and support of mainframe applications (z/OS, COBOL, JCL, DB2, VSAM) integrated with modern services
- Own end-to-end SDLC delivery: design → build → test → deploy → operate
- Serve as technical authority and SME across mainframe and modernization initiatives
2. Solution Architecture & Design Governance
- Define and enforce end-to-end solution architecture across:
- Mainframe systems
- ZConnect API layer
- ZDIH / data integration platforms
- Distributed/cloud ecosystems
- Own creation and governance of:
- Solution Architecture Documents (SAD)
- Component, integration, and data flow diagrams
- Ensure:
- Loose coupling between legacy and modern systems
- API-first and event-driven design where applicable
- Scalability, resiliency, and performance considerations
- Conduct architecture reviews and design approvals before development initiation
3. DevOps, GitLab & Pipeline Ownership
- Lead adoption and governance of GitLab-based CI/CD pipelines
- Define and enforce:
- Branching strategies (feature / release / hotfix)
- Merge request standards and approvals
- Code quality gates (Sonar, coverage thresholds)
- Drive pipeline standardization and automation, reducing manual steps
- Own pipeline troubleshooting and continuous improvement
4. Modernization & Integration (ZConnect / ZDIH)
- Lead delivery of z/OS Connect APIs enabling mainframe services
- Drive adoption of ZDIH and hybrid integration patterns
- Identify opportunities to:
- Decouple legacy logic
- Enable reusable APIs and services
- Ensure secure and scalable integration with distributed platforms
5. QA Engineering & Quality Practices
Test Strategy & Governance
- Define and enforce end-to-end QA strategy, including:
- Unit testing
- Integration testing
- System / end-to-end testing
- Regression testing
- Ensure test strategy is documented and approved prior to development
Automation & DevOps Integration
- Drive test automation integrated into GitLab pipelines:
- Automated unit tests
- Regression test suites
- Pipeline-based validation and quality gates
- Enforce shift-left testing practices across the team
Quality Engineering Standards
- Establish and enforce:
- Code quality standards (static analysis, peer review)
- Test coverage thresholds
- Defect lifecycle discipline and root cause analysis
- Ensure test data strategy and environment stability
Release & Production Quality
- Define release validation criteria:
- Pre-production validation
- Deployment smoke tests
- Post-deployment verification
- Reduce:
- Production defects
- Rework and regression failures
6. Engineering Excellence & Automation
- Drive automation-first mindset:
- Minimize manual batch/process work
- Automate validation, deployments, and monitoring
- Improve:
- Cycle time
- Deployment consistency
- Operational resilience
7. Team Leadership & Talent Development
- Lead and mentor engineers across:
- Mainframe technologies
- DevOps practices
- Modern integration stacks
- Build culture of:
- Accountability and ownership
- Peer review and quality discipline
- Continuous learning and upskilling
8. Stakeholder & Delivery Management
- Translate business requirements into scalable technical solutions
- Manage:
- Backlog prioritization
- Sprint execution
- Delivery commitments
- Ensure adherence to:
- SDLC controls
- Audit and compliance requirements
9. Strategic Leadership & Technology Direction (NEW)
- Define and drive technology strategy for mainframe modernization and hybrid architecture (Mainframe + ZConnect + ZDIH + DevOps)
- Align engineering roadmap with business priorities, cost optimization, and risk reduction goals
- Identify and execute opportunities to:
- Reduce technical debt
- Simplify legacy processes
- Improve platform scalability and resiliency
- Lead transformation initiatives from:
- Batch/report-driven systems → API-driven and data-integrated platforms
- Influence cross-team and enterprise decisions on standards, tooling, and architecture
10. Metrics-Driven Engineering & Execution Discipline (NEW)
- Establish and enforce a metrics-driven operating model across engineering and delivery
- Define, track, and report on key performance indicators (KPIs), including:
- Sprint predictability (≥90% commitment adherence)
- Deployment frequency and lead time
- Defect density and production leakage
- Test automation coverage
- Pipeline success/failure rates
- Drive data-based decision making for:
- Capacity planning
- Prioritization and backlog management
- Continuous improvement initiatives
- Implement regular performance reviews (team and system-level) using measurable outcomes
- Ensure all initiatives have:
- Clear success criteria
- Defined milestones
- Traceable outcomes aligned to OKRs
Required Qualifications
Technical Skills
- Strong experience in Mainframe technologies
- z/OS, COBOL, CICS, JCL, VSAM, Easytrieve+
- Experience with:
- z/OS Connect (ZConnect)
- ZDIH / data integration / hybrid architectures
- Hands-on expertise in:
- GitLab CI/CD pipelines, branching, release management
- DevOps practices
- Experience integrating with:
Leadership & Delivery Skills
- Proven experience leading engineering teams / technical squads
- Strong understanding of:
- Agile / Scrum
- SDLC governance
- Ability to:
- Drive execution discipline
- Balance legacy stability and modernization
Preferred Qualifications
- Experience in solution architecture / system design leadership
- Exposure to:
- Cloud (Azure / OpenShift)
- Event-driven / API-first architecture
- Familiarity with:
- Enterprise schedulers (CA7, Automic)
- Observability / SRE practices
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