Lead Infrastructure Engineer, Infrastructure Monitoring

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Columbus, OH
Posted: 42 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $179k

$100k most similar roles pay here $249k

This listing doesn't post a salary. Most similar roles pay $144,350–$213,962.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Lead Infrastructure Engineer, Infrastructure Monitoring

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Lead Infrastructure Engineer- Infrastructure Monitoring joins the Enterprise Observability Platforms team to build and operate a strategic monitoring platform that enhances service resilience and provides actionable operational insights. This role involves engineering infrastructure monitoring capabilities across Linux, Windows, and Network estates while modernizing event-to-incident workflows through automation and AIOps. The engineer will design telemetry collection using OpenTelemetry patterns, develop production code for configuration management, and implement Infrastructure-as-Code using Terraform. Key responsibilities include improving signal quality through baselining and noise reduction, managing platform health via root cause analysis, and ensuring secure deployments in hybrid cloud environments. Required skills include proficiency in Python, Ansible, PowerShell, and Bash, alongside experience with metrics, logs, and events. The role addresses the challenge of providing reliable observability across complex infrastructure while maintaining strict security and auditability standards.

Skills

Infrastructure Monitoring OpenTelemetry Python Ansible PowerShell Bash Terraform CI/CD Infrastructure-as-Code Linux Windows SQL Server Oracle Cassandra Splunk Dynatrace Grafana Prometheus Kubernetes AIOps

What you'll do

Engineer, operate, and improve the firm’s Infrastructure Monitoring platforms to ensure availability, performance, and security.
Build and manage enterprise-grade monitoring capabilities across Linux, Windows, and complex network estates.
Design and implement telemetry collection for metrics, logs, and events using OpenTelemetry patterns.
Develop standardized onboarding patterns for agents, collectors, dashboards, and alert policies at scale.
Improve monitoring signal quality through baselining, noise reduction, and topology alignment to enhance event-to-incident workflows.
Write, debug, and maintain secure production code and configuration management scripts using Python, Ansible, or PowerShell.
Automate platform operations and reduce toil using CI/CD pipelines and Infrastructure-as-Code deployment patterns.
Manage production health by leading triage efforts, performing root cause analysis, and implementing preventative engineering improvements.

What we're looking for

Formal training or certification in infrastructure engineering concepts and 5+ years of applied experience.
Proficiency in administering, troubleshooting, and performing performance analysis on Linux and Windows operating systems in regulated environments.
Experience delivering and operating enterprise-scale Infrastructure Monitoring solutions across Linux, Windows, and Network estates.
Expertise in observability and telemetry concepts including metrics, logs, events, and OpenTelemetry collection patterns.
Proficiency in scripting and development using Python, Ansible, PowerShell, and Bash for automation and CI/CD workflows.
Experience implementing Infrastructure-as-Code (IaC) and configuration management using tools such as Terraform.
Experience operating in hybrid infrastructure environments including on-prem platforms and public or private clouds.
Ability to use enterprise-authorized AI capabilities to support engineering workflows while ensuring data security and validation.

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