Senior Observability Engineer — ArcGIS Enterprise

esri; Redlands (CA); On-site; USD 94,000 - 159,000; Full time

Benefits offered by this job

Health benefits

401(k) and profit-sharing

Vacation leave

Paid holidays

Job summary

Esri in Redlands, CA is seeking a Product Engineer for observability to design and implement observability patterns for ArcGIS Enterprise, leveraging AI and data-driven techniques for automated root cause analysis and intelligent sizing recommendations.

You will work with cross-functional teams to translate customer needs into technical requirements, design end-to-end observability pipelines, and contribute to RCA capabilities and data-driven sizing models.

Qualifications

• 5+ years of experience with ArcGIS Enterprise and observability.
• Experience designing end-to-end observability pipelines.
• Experience with test planning and test automation.
• Translating customer needs into technical requirements.

Responsibilities

• Translate customer needs into technical requirements for ArcGIS Enterprise observability.
• Design and evolve observability pipelines across metrics, logs, traces, and events.
• Contribute to AI-driven RCA capabilities and sizing models.
• Collaborate with cross-functional teams on software releases and QA.

Skills

Observability patterns

Problem solving

Analytical skills

Team collaboration

Time management

Education

Bachelor's degree in computer science, software engineering, information systems, or related field

Master's degree in computer science or related field

Tools

Prometheus

Grafana

Python

Java

Job description

Esri in Redlands, CA is seeking a Product Engineer for observability to design and implement observability patterns for ArcGIS Enterprise, leveraging AI and data-driven techniques for automated root cause analysis and intelligent sizing recommendations.

You will work with cross-functional teams to translate customer needs into technical requirements, design end-to-end observability pipelines, and contribute to RCA capabilities and data-driven sizing models.