Senior Backend Engineer - Scalable Data & ML Services

Disney; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Disney Entertainment and ESPN Product & Technology is seeking a Sr Product Software Engineer to build and scale backend services in a fast-paced environment. You will design and implement Java/Scala-based systems, contribute to data pipelines, and help deploy machine learning models that power consumer experiences.

Join a distributed team responsible for high-availability services, performance optimization, and robust testing practices.

Qualifications

• BS in Computer Science, Engineering, or a related field.
• MS in Computer Science, Engineering, or a related field.

Responsibilities

• Design, build, and maintain backend services using Java and Scala.
• Develop scalable systems supporting data processing and User Enablement capabilities.
• Maintain and deploy machine learning models associated with critical services.
• Improve service performance, scalability, and operational excellence.
• Diagnose and resolve production issues across distributed backends.
• Collaborate with cross-functional teams including product, data, platform, and infra teams.
• Develop and maintain automation test frameworks and software quality practices.
• Contribute to architecture discussions to support long-term business growth.

Skills

Java/Scala backend

Distributed systems

Data processing

ETL pipelines

ML model deployment

Database design

Performance optimization

Testing frameworks

Communication

Independent worker

Education

Bachelor's degree in CS/Engineering

Master's degree in CS/Engineering

Job description

Disney Entertainment and ESPN Product & Technology is seeking a Sr Product Software Engineer to build and scale backend services in a fast-paced environment. You will design and implement Java/Scala-based systems, contribute to data pipelines, and help deploy machine learning models that power consumer experiences.

Join a distributed team responsible for high-availability services, performance optimization, and robust testing practices.