Product Software Engineer I

Product Software Engineer I

On any given day at Disney Entertainment & ESPN Technology, we're reimagining ways to create magical viewing experiences for the world's most beloved stories while also transforming Disney's media business for the future. Whether that's evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney's unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.

The Product & Data Engineering team is responsible for end-to-end development for Disney's world-class consumer-facing products, including streaming platforms Disney+, Hulu, and ESPN+, and digital products & experiences across ESPN, Marvel, Disney Studios, NatGeo, and ABC News. The team drives innovation at scale for millions of consumers around the world across Apple, Android, Smart TVs, game consoles, and the web, with our platforms powering core experiences like personalization, search, messaging and data.

A few reasons why we think you'd love working for Disney Entertainment & ESPN Technology:

• Building the future of Disney's media business: DE&E Technologists are designing and building the infrastructure that will power Disney's media, advertising, and distribution businesses for years to come.
• Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu to ABC News and Entertainment, to ESPN and ESPN+, and much more.
• Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.

Job Summary:

Sitting inside the Product and Engineering team, the Client-Data team bridges data requirements between our front-end applications and engineering services. Our work spans software engineering, machine learning, and data science at scale — from platform health monitoring and performance tracking for new releases to synchronizing instrumentation, metrics, and data-related decisions across platforms. Day to day, our work directly impacts the business through application engagement monitoring, anomaly detection, and more.

The team leverages AI-powered tools and generative AI to accelerate development, automate data quality checks, and surface actionable insights from telemetry data at scale. This includes integrating AI/ML products — intelligent anomaly detection, AI-assisted code generation, and natural language interfaces for data exploration — into both internal tooling and consumer-facing experiences. Team members are expected to stay current with the evolving AI landscape and identify opportunities to apply foundation models, RAG, and other AI-driven approaches to improve observability, streamline instrumentation pipelines, and drive smarter, data-informed decision-making.

Responsibilities and Duties of the Role:

• Create and maintain optimal data pipeline architecture
• Algorithm Development and Maintenance
• Develop Best Practices and Documentation
• Perform data analysis and data science projects for stakeholders

Basic Qualifications:

• Experience with big data tools including Databricks, Snowflake, or similar.
• Service Reliability/Operational experience running large-scale high-performance systems & Internet services
• Ability to write and maintain reliable and understandable code in SQL, Python, Scala, or other languages.

Preferred Qualifications:

• 1-2 years of software engineering, machine learning or data science experience
• Familiarity with the end-to-end data lifecycle: from client-side event generation to backend processing and consumption by Data Science models.
• Experience leveraging ML-driven automation to build internal tooling, streamline data pipelines, or enhance observability and monitoring capabilities.
• Familiarity with AI/ML frameworks and platforms and demonstrated ability to evaluate and integrate AI products into existing engineering workflows.

Required Education:

Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field of study, or equivalent work experience.