Lead Software Engineer - Observability & AI-Driven Data

ESPN; Seattle (WA); On-site; USD 166,000 - 222,000; Full time

Job summary

Disney Entertainment and ESPN Product & Technology seeks a Lead Software Engineer focused on observability tooling and data integrations. You will guide design and delivery of multi-component systems for collecting and analyzing critical system data, working with engineers across teams to improve visibility, deployment, and performance.

You will leverage AI tools to enhance workflows and drive adoption across the engineering lifecycle, evaluating emerging technologies in practical ways for

Qualifications

• 7+ years of professional software development experience.
• Architecting, building, and maintaining production apps with modern languages and frameworks.
• Strong problem-solving skills with ability to lead others through complex technical problems.
• Experience with modern development practices and CI/CD.

Responsibilities

• Own and lead the development of multi-component observability tools and data pipelines.
• Set architectural direction and collaborate across teams to improve monitoring and data analysis.
• Establish AI-assisted development practices to improve engineering efficiency.
• Document requirements for engineering data models and integrations for parallel execution.
• Lead issue resolution and perform root-cause analysis affecting related systems.
• Deliver data-driven insights to improve system performance and reliability.
• Mentor senior engineers and reinforce code quality and processes.

Skills

Golang

TypeScript

Python

Java

C++

Rust

React

Angular

Education

BS/MS in Computer Science or Engineering

Tools

GitHub

Kubernetes

Terraform

CloudFormation

Job description

Disney Entertainment and ESPN Product & Technology seeks a Lead Software Engineer focused on observability tooling and data integrations. You will guide design and delivery of multi-component systems for collecting and analyzing critical system data, working with engineers across teams to improve visibility, deployment, and performance.

You will leverage AI tools to enhance workflows and drive adoption across the engineering lifecycle, evaluating emerging technologies in practical ways for