Sr Software Engineer

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.

The Personalization and Recommendations team builds systems that provide distinctly tailored experiences to viewers across our streaming products around the globe. We use Machine Learning and Artificial Intelligence to create powerful content discovery experiences across web, mobile, and living room devices. Through the development of scalable, intelligent, and responsive systems, our team is at the forefront of positively differentiating our viewer experiences each and every day. We are on a mission to connect viewers with content they love.

The Data and Infrastructure team is central to that mission: we provide the data to our Machine Learning models and downstream client teams that enable the most relevant content to viewer matching possible. Our challenge is to source and provide the highest quality data to feed into our recommendation systems, and build out the infrastructure required to deliver personalized data on every request, every time for our hundreds of millions of subscribers around the world.

As a Senior Software Engineer in this role, you’ll apply your passion for data, along with your previous experience working with large scale, low-latency backend distributed systems and data stores to help our team meet this goal. You’ll collaborate closely with machine learning engineers, data engineers and software engineers, as well as project managers and product managers to create the best experiences possible for our viewers.

If this sounds like you, we’d love to hear from you!

What You’ll Do:

• Design, build and maintain large-scale, low-latency data stores that power personalized content recommendations at global scale

• Develop and optimize backend APIs and services that reliably deliver personalization data to downstream clients for our hundreds of millions of streaming subscribers

• Craft and evolve data production and ingestion pipelines to ensure timely, performant and economical persistence of foundational personalization data

• Collaborate with machine learning engineers to design and implement elegant solutions used for feature storage, retrieval, and online inference

• Champion operational excellence by leading observability best practices and participating in an on-call rotation for our tier one critical services

What You’ll Bring:

Basic Qualifications

• Bachelor’s degree in Computer Science (or related field), or equivalent work experience

• 5+ years of related experience working with large scale distributed systems and data at scale

• Strong grasp of computer science fundamentals (data structures, algorithms, design patterns, etc.)

• Strong programming skills in Java, Python, or comparable object-oriented language

• Hands-on experience with NoSQL data stores (e.g. DynamoDB, Cassandra, ScyllaDB, or other)

• Familiarity with Databricks or equivalent large-scale data processing platforms

• Demonstrated knowledge of caching technologies

• Demonstrated knowledge of operating within a Public Cloud Provider (e.g. AWS, Microsoft Azure, Google Cloud)

• Demonstrated knowledge of source control systems and CI/CD pipelines

• Strong communication skills, both written and verbal

Preferred Qualifications

• Experience designing performant database schemas at scale

• Proficiency working in Databricks to build data pipelines

• Experience with distributed data processing frameworks, such as Apache Spark

• Demonstrated knowledge of messaging technologies (e.g. Kafka, Kinesis, SQS, or other)

• Familiarity with recommendation systems industry architectures and best practices

• Hands-on experience using AI to accelerate design and development

The hiring range for this position in Glendale, CA is $138,900 - $186,200, for Santa Monica, CA is $138,900 - $186,200, for Seattle, WA is $145,400 - $195,000, and for New York, NY is $145,400 - $195,000, and for San Francisco, CA is $152,100 - $203,900. 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.