Join a dynamic team focused on building cutting-edge observability and self-service platforms for Entertainment & ESPN engineering. This role offers the opportunity to develop expertise in Python, AWS, and modern observability practices, working alongside seasoned engineers. You will be part of an organization comprising Technical Operations, Reliability Platforms, and Observability & Platform teams, each contributing to large-scale 24x7 application management with clear operational objectives.

Your background should include solid Python fundamentals and experience with AWS, systems programming, the software development lifecycle, incident response, and observability tools like Datadog, CloudWatch, and Grafana. Within the Observability & Platform team, you will receive technical guidance from lead and senior engineers, enhancing your skills through pairing, code reviews, and mentorship. This role reports to the Director, Product Software Engineering.

Key responsibilities include developing features for telemetry pipelines, dashboards, and self-service tooling, ensuring production-quality code with robust test coverage. You will also build and maintain backend APIs and integrations in Python, contribute to secure IAM permission workflows and cloud automation, and assist in maintaining operational data pipelines and reliability reporting.

Additionally, you will instrument services, tune alerts and dashboards, and participate in the on-call rotation for platform services. Growth opportunities are provided through pairing with senior engineers and code review processes, fostering expertise in platform engineering and cloud security.

A minimum of 3 years of professional software engineering experience is required, along with proficiency in Python development focused on maintainable, tested code. Foundational experience with AWS and Unix/Linux environments is essential.

Exposure to monitoring and observability tools such as Datadog, Prometheus, Grafana, or CloudWatch, as well as CI/CD pipelines, Docker, and containerization concepts is expected. Strong written and verbal communication skills are necessary, alongside a genuine interest in learning platform engineering practices.

While not strictly required, preferred qualifications include frontend exposure with React or TypeScript, familiarity with data pipelines like Spark or Airflow, or machine learning concepts. Experience with AWS IAM policies, cloud security, and leveraging AI-assisted development tools is also a plus. A Bachelor’s degree in a relevant field or equivalent training/work experience is necessary.