Reach, Scale & Impact:

More than ever, Disney's technology and products serve as a signature doorway for fans' connections with the company's brands and stories. Disney+. Hulu.

ESPN. ABC. ABC

News…and many more. These products and brands - and the unmatched stories, storytellers, and events they carry - matter to millions of people globally.

Innovation:

We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

Job Summary:

Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity. Join the Observability & Insights group and help build the telemetry, monitoring, and insights platforms that keep Disney's large-scale streaming services reliable — including Disney+, Hulu, ESPN, ABC, ABC News, and related products. As a Software Engineer I, you will implement well-scoped features, fix bugs, and improve tooling under the guidance of senior engineers. You'll contribute to metrics, logs, traces, dashboards, and alerting workflows that help engineering teams across Disney Streaming understand system health and respond to incidents faster. This is an ideal role for an early-career engineer who wants hands-on experience with distributed systems, cloud infrastructure, and observability at scale. You'll grow through code reviews, design discussions, pair programming, and on-call shadowing — while delivering real value to a platform team that reduces operational toil through automation and modern developer workflows. Responsibilities and Duties of the

Role:

Implement and Maintain Observability Features Develop, test, and document features within existing observability codebases (metrics, logs, traces, dashboards, alerting, and telemetry pipelines). Fix bugs and address technical debt in assigned components with support from senior teammates. Write clean, readable, and well-tested code that follows team standards and integrates with established observability frameworks. Learn and apply patterns for high-volume, low-latency telemetry ingestion and storage. Improve Visibility for Service Teams Assist in instrumenting services and validating telemetry quality (metrics, logs, traces) alongside partner engineering teams. Build and update dashboards, reports, and visualizations that surface system health and operational trends. Help tune alerts and reduce noise under guidance from senior engineers and incident response partners. Learn Platform Engineering Practices Participate in code reviews — both giving and receiving constructive feedback. Contribute to technical design discussions for small-to-medium features; document your work for maintainability and team onboarding. Gain exposure to cloud infrastructure (AWS), container orchestration (Kubernetes), and Infrastructure as Code (IaC) through guided implementation tasks. Shadow on-call rotations and incident response workflows to build operational awareness. Collaborate and Grow Break down assigned work into clear tasks, ask questions early, and communicate progress and blockers proactively. Partner with teammates across Observability & Insights and service engineering teams to deliver incremental improvements.

Participate in team rituals:

standups, sprint planning, retrospectives, and knowledge-sharing sessions. Develop foundational skills in reliability engineering concepts: SLIs, SLOs, post-incident reviews, and blameless culture.

Basic Qualifications:

Proficiency in at least one backend or systems programming language: Go or Python (coursework, internships, and personal projects count). Foundational understanding of software development practices: version control (Git), unit testing, debugging, and working within an existing codebase. Basic familiarity with cloud computing concepts and interest in learning AWS and Kubernetes in production environments.

Introductory understanding of observability concepts:

metrics , logs , tracing , and alerting — or strong motivation to learn them quickly. Ability to communicate clearly, accept feedback, and collaborate effectively in a distributed engineering team.

Preferred Qualifications:

0-2 years of professional software engineering experience, or completion of a relevant internship, co-op, or new-graduate program with demonstrated project work. Internship, co-op, or project experience related to observability , SRE , DevOps , or platform engineering . Exposure to observability tools or standards: Grafana , Prometheus, OpenTelemetry , Datadog , New Relic, or similar. Experience with distributed systems , data pipelines , or event-driven architectures (academic, internship, or side projects). Contributions to open source , hackathons, or personal projects that demonstrate curiosity and initiative. Coursework or experience with databases , streaming systems (e.g., Kafka), or CI/CD pipelines. Familiarity with AI-assisted development workflows and a growth mindset toward modern engineering practices.

Required Education:

Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a comparable field of study, or equivalent work experience. The hiring range for this position in Glendale, CA is $97,500 to $130,700 per year and in New York, NY is $102,100 to $136,900 per year based on a 40 hour work week. The amount of hours scheduled per week may vary based on business needs. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. 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