Disney Entertainment and ESPN Product & Technology

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Here are a few reasons why we think you’d love working here:

Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come. 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.

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.

Job Summary:

Sitting inside the Product Engineering team, the Client-Data team plays a pivotal role in bridging the data requirements between our diverse portfolio of front-end applications, and engineering services teams. Our work encompasses the application of software engineering, machine learning and data science at scale, addressing challenges such as platform health monitoring and ongoing performance tracking for new application releases. We collaborate closely with stakeholders to validate product specifications, ensuring clarity and precision, while also synchronizing data-related decisions, instrumentation, and metrics across various platforms. Day to day tasks impact many aspects of the business, such as monitoring application engagement or tracking anomalous usage patterns.

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

Required Education, Experience/Skills/Training:

Basic Qualifications

• 3+ years of software engineering, machine learning or data science experience
• Experience with big data tools including Databricks, Snowflake, or similar.
• Knowledge of systems applications, server architecture, cloud technologies, and web applications.
• Experience working cross-functionally with teams of different levels of expertise
• 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

Familiarity with the end-to-end data lifecycle: from client-side event generation to backend processing and consumption by Data Science models.

Required Education

Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience

The hiring range for this position in New York City is $123,000 - $165,000 per year and in San Francisco, CA is $128,700 - $172,500 per year. 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. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.