Mainframe DB2 Replication Engineer - Hybrid

Nexiva•Phoenix, AZ

2d•Hybrid

About The Position

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.

Requirements

DB2 for z/OS
ZDIH MIPS reduction / optimization projects
UNIX system service including installing patch on UNIX
UNIX scripting
RACF
Hands-on experience with replication technologies: IBM InfoSphere Data Replication (IIDR) / CDC Q Replication (preferred)
Replication architecture and data flow design
Change Data Capture (CDC) concepts
Strong troubleshooting skills in: Data consistency issues, Performance and replication latency
JCL, TSO/ISPF, SDSF
Mainframe batch and online environments
LinkedIn and Financial Domain Exp

Nice To Haves

MQ / messaging systems
ETL and data warehousing platforms
Monitoring tools
Automation (REXX, Python, scripting)
Cloud or hybrid data architecture
Large-scale data migration or modernization programs

Responsibilities

Design, install, configure, and maintain DB2 replication solutions across mainframe and distributed platforms
Build and manage source-to-target replication pipelines
Configure replication components: Capture processes, Apply processes, Control servers
Implement: Unidirectional and bidirectional replication setups, Real-time and near-real-time data synchronization solutions
Troubleshoot and resolve: Data inconsistencies, Replication failures, Queue backlogs, Network interruptions
Perform root cause analysis and implement corrective actions
Provide L2/L3 support for production incidents
Tune replication processes to: Reduce latency, Optimize resource utilization, Minimize impact on source systems
Optimize: Data capture efficiency, Apply performance, Network usage
Support integration across: DB2 z/OS and DB2 LUW systems, Distributed databases, message queues, and ETL platforms
Work closely with: DBAs, Application teams, Data engineering and BI teams