Morningstar Inc.

Morningstar Inc.

Lead Software Engineer, Customer Experience & Reliability

Chicago

Sponsorship not specified$300k-$600kDetected 27 days ago
JavaScriptC#.NETDistributed SystemsAWSIncident ResponseCustomer SuccessLeadershipCommunicationCollaborationProblem SolvingMentoring

About the role

  • This role offers a unique mix of technical leadership and hands-on engagement, allowing you to influence outcomes while staying close to the technology.
  • In most of our locations, our hybrid work model is four days in-office each week.
  • No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

Responsibilities

  • Lead cross-functional debugging sessions across Engineering, Customer Success Managers, Operations, and Support.
  • Support during incidents by tracking decisions, risks, and next steps.
  • Lead Production Issue Ownership
  • Maintain deep technical fluency to:
  • Review proposed fixes and designs with a focus on reliability, operability, and customer impact.
  • Manually reproduce customer issues, isolate root causes, and deploy fixes under time pressure while partnering with L1/L2 support teams to resolve high-priority advisor tickets.
  • Recognize recurring issue patterns and provide feedback to feature development teams to drive systemic improvements.
  • Identify systemic weaknesses and partner with engineering teams to improve observability, diagnostics, and operational readiness.
  • Support and influence emerging automation or AI-assisted diagnostic workflows.
  • Mentor engineers and support teams on effective incident handling and production readiness.

Requirements

  • Hands-on experience with C#,.NET /.NET Core
  • Experience working with distributed systems in production
  • Familiarity with AWS-hosted systems and cloud-based architectures

Compensation

  • At Morningstar we believe people are at their best when they are at their healthiest.

This listing is sourced directly from Morningstar Inc.'s careers page and normalized into a canonical job model.