Position Overview
Overview:
We are seeking an experienced Mainframe DB2 Replication Engineer to design, implement, and support data replication solutions across IBM z/OS and distributed environments. This role is responsible for ensuring reliable, real-time data synchronization, high availability, and data consistency for mission-critical banking applications.
Responsibilities:
Replication Design & Implementation
- Design, install, configure, and maintain DB2 replication solutions across mainframe and distributed platforms
- Build and manage source-to-target replication pipelines
- Configure replication components:
o Capture processes
o Apply processes
o Control servers
o Unidirectional and bidirectional replication setups
o Real-time and near-real-time data synchronization solutions
Troubleshooting & Support
- Troubleshoot and resolve:
o Data inconsistencies
o Replication failures
o Queue backlogs
o Network interruptions
- Perform root cause analysis and implement corrective actions
- Provide L2/L3 support for production incidents
Performance Optimization
- Tune replication processes to:
o Reduce latency
o Optimize resource utilization
o Minimize impact on source systems
o Data capture efficiency
o Apply performance
o Network usage
Integration & Data Architecture
- Support integration across:
o DB2 z/OS and DB2 LUW systems
o Distributed databases, message queues, and ETL platforms
o DBAs
o Application teams
o Data engineering and BI teams
Required Qualifications:
o DB2 for z/OS
o ZDIH
o MIPS reduction / optimization projects
o UNIX system service including installing patch on UNIX
o UNIX scripting
o RACF
- Hands-on experience with replication technologies:
o IBM InfoSphere Data Replication (IIDR) / CDC
o Q Replication (preferred)
o Replication architecture and data flow design
o Change Data Capture (CDC) concepts
- Strong troubleshooting skills in:
o Data consistency issues
o Performance and replication latency
o JCL, TSO/ISPF, SDSF
o Mainframe batch and online environments
Preferred Experience:
o MQ / messaging systems
o ETL and data warehousing platforms
o Monitoring tools
o Automation (REXX, Python, scripting)
o Cloud or hybrid data architecture
o Large-scale data migration or modernization programs
Real-time data streaming architecture