Production Systems Reliability Engineer

Harvey Nash; Fremont (CA); On-site; USD 90,000 - 120,000; Full time

Job summary

Harvey Nash in Fremont, CA is seeking an Internal Production Support Engineer to ensure stability and performance of internal systems. You will resolve incidents, monitor platforms with ITRS, Splunk and Datadog, and drive RCA for recurring issues while automating repetitive tasks with Shell and Python.

Responsibilities include supporting releases, coordinating with development and operations, and maintaining procedures to minimize downtime and maximize uptime across the internal tech stack.

Qualifications

• 3-5 years of experience in manufacturing, equipment troubleshooting, or technical support.
• Strong troubleshooting skills, ownership during incidents, and ability to remain calm under pressure.

Responsibilities

• Ensure stability, performance, and availability of internal machines and equipment.
• Incident management and troubleshooting using monitoring tools such as ITRS, Splunk, and Datadog.
• Root cause analysis (RCA) for recurring production incidents and implementation of permanent fixes.
• Automation and scripting (Shell, Python) to reduce manual and repetitive tasks.
• System maintenance, including batch processes, upgrades, and ensuring server/network functionality.
• Cross-functional communication and documentation of procedures.
• Supporting release deployments and user acceptance testing (UAT).

Skills

Troubleshooting

Ownership during incidents

Calm under pressure

Tools

ITRS

Splunk

Datadog

Shell

Python

Job description

Harvey Nash in Fremont, CA is seeking an Internal Production Support Engineer to ensure stability and performance of internal systems. You will resolve incidents, monitor platforms with ITRS, Splunk and Datadog, and drive RCA for recurring issues while automating repetitive tasks with Shell and Python.

Responsibilities include supporting releases, coordinating with development and operations, and maintaining procedures to minimize downtime and maximize uptime across the internal tech stack.