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https://www.gevinsttech.comJobs at Gevinst Technologies

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We are seeking experienced Mainframe Z/OS System Programmer/Admin to manage z/OS environments.
Job Title - Mainframe z/OS System Programmer
Experience - 4-8 Years
Location - Bangalore, Chennai, Pune [Hybrid/Remote]
Notice Period - Immediate Joiners Preferred
Job Overview
We seek an experienced Mainframe z/OS System Programmer to manage and support z/OS environments. The role includes system upgrades, performance monitoring, installations, troubleshooting, and expertise in ISV tools, JCL, scripting, and system utilities.
Key Responsibilities
- Administer and support z/OS mainframe systems.
- zOS install and upgrade, PTF patch apply
- ISV tools installation and upgrade
- Parmlib, Proclib
- Perform SMP/E & Non-SMP/E installation of ISV products and manage upgrades (z/OS V2.5/V3.1).
- Configure and manage JES3/JES2, Sysplex, and related components.
- Configure and monitor TSO/E, ISPF, and basic scripting in REXX/CLIST.
- Plan and execute z/OS upgrade and maintenance roadmaps.
- Monitor system performance using tools like SMF and z/OS Health Checker.
- Support mainframe storage management (SMS/DFSMS) and backup/recovery processes.
- Resolve incidents using appropriate tools and perform diagnostics as required.
- Candidates with prior experience as a z/OS System Programmer, specializing exclusively in z/OS administration, are encouraged to apply.
Preferred Technical Skills
1. Mainframe zOS Admin
2. zOS install and upgrade, PTF patch apply
3. ISV tools installation and upgrade
4. Parmlib, Proclib
Note
The candidate must have prior experience working as a z/OS System Programmer with hands-on expertise in managing complex mainframe environments.

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We Enable and empower our partners to engage their clients through smart technology. Use of technology innovations designed to squeeze out savings and efficiency from the current insurance industry model.The belief driving us is that the insurance industry is ripe for innovation and disruption. We offer ultra-customized tools and using new streams of data from internet-enabled devices to dynamically price premiums according to observed behavior.
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