Monitor and analyze real-time z / OS system health and performance across CPU, memory, DASD, and WLM-managed workloads using tools such as RMF, SMF, IzPCA, SmartIS, and MICS .
Detect, troubleshoot, and resolve resource anomalies, workload degradation, and system bottlenecks .
Drive performance tuning initiatives by adjusting WLM service definitions, dispatching priorities, and workload placements.
Contribute to capacity planning — forecasting and modeling workload resource demands and optimizing infrastructure utilization.
Support cost modeling, vendor reporting (SCRT) , and infrastructure sizing.
Analyze and visualize performance data to create dashboards, KPIs, and executive summaries using Excel (Pivot Tables, PowerPivot, VLOOKUPs) and PowerPoint .
Collaborate with infrastructure, DevOps, and operations teams to ensure optimal workload performance and provide technical insights.
Participate in on-call rotations and contribute to the migration of performance / capacity tools to Git / DevOps pipelines .
Required Skills & Experience
10+ years of total mainframe systems experience, with 6+ years focused on performance engineering and capacity planning.
Proven expertise in mainframe performance monitoring, observability, and tuning in large multi-LPAR, multi-processor Parallel Sysplex environments.
Strong hands-on experience with WLM (Workload Manager) , SMF / RMF data , and z / OS performance tools .
Proficiency in COBOL, JCL, and DB2 (for understanding workloads, not development).
Strong knowledge of batch processing and job scheduling .
Excellent data analysis and visualization skills using MS Excel and PowerPoint .
Strong communication and presentation skills to engage global teams and leadership.
Good-to-Have Skills
Python scripting for automation or data analysis.
REXX and / or Java experience on mainframe.
Exposure to DevOps pipelines or Git-based deployment.
Experience with iZPCA , MICS , ADABAS , or IBM SCRT reporting tools.
Prior experience in retail, telecom, or healthcare domains (BFSI not mandatory).
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