Fidelity investments
Principal Engineer
Overview
Principal Engineer, Mainframe CICS/MQ/WAS Performance and Capacity focusing on hands-on performance analysis, problem determination, monitoring, reporting, and automation across CICS, MQ, WebSphere Application Server (WAS), Liberty Java Batch, Compute Grid, Kafka MQ connectors, and Operational Decision Manager (ODM).
About Fidelity investments
The Fidelity Mainframe Capacity and Performance team is responsible for capacity modeling, forecasting, performance analysis, system configuration tuning, monitoring, and L2/L3 problem determination supporting Fidelity’s large complex IBM z Systems infrastructure.
Requirements & Eligibility
- Hands-on experience supporting or analyzing one or more IBM mainframe middleware domains such as CICS, MQ, WAS, Liberty, Compute Grid, Kafka integration, or ODM.
- Working knowledge of z/OS, SMF/RMF data, GP/zIIP use, memory, Coupling Facility, zFS, log streams, and subsystem interactions.
- Experience with performance monitoring, problem determination, capacity reporting, application support, systems programming, or production engineering in a complex enterprise environment.
- Experience using one or more analysis platforms such as SYSVIEW, IntelliMagic, OMEGAMON, SAS/MXG, Grafana, Datadog, Prometheus, VictoriaMetrics, PostgreSQL, or equivalent tools.
Key Responsibilities
- Analyze CICS performance and behavior, including internal functions, region activity, transactions, programs, files, queues, dispatching, thresholds, and how application programs use CICS services.
- Analyze IBM MQ behavior across queue managers, CHINIT address spaces, queues, channels, and connections to distributed or off-mainframe conversation partners.
- Support WAS on z/OS, Liberty, Java Batch (JSR 352), and Compute Grid workloads.
- Support performance analysis of Kafka MQ connectors, brokers, channels, message flow, and tunable settings on the MQ and Kafka sides.
- Develop and maintain Grafana dashboards and support metric collection using Python and Prometheus with VictoriaMetrics or PostgreSQL data stores and Datadog reporting where applicable.
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