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About the Role

The Discovery Data team builds systems that provide tailored experiences to viewers across streaming products globally, using Machine Learning and Artificial Intelligence for content discovery and seamless browse experiences. The Core Data team provides the foundational data layer to ML models and User Experience APIs to enable optimal personalized experiences for millions of subscribers.

Responsibilities

• Design, craft and own high quality foundational datasets to produce reliable, meaningful inputs for machine learning models and subscriber experiences
• Source, analyze and validate diverse upstream data sources from upstream partner teams and raw signals using exploratory data analysis
• Identify and build new user and content data features for recommendation systems through collaboration with machine learning engineers
• Enhance existing feature quality through experimentation, analysis and iterative development
• Build, optimize and maintain large scale data processing jobs, pipelines and workloads
• Improve data quality and reliability through implementing checks, anomaly detection, testing, monitoring and alerting
• Contribute to operational excellence by following observability best practices and participating in an on-call rotation to support critical production data pipelines

Requirements

• Bachelor’s degree in Computer Science (or related field), or equivalent work experience
• 3 years of experience working with large scale data workloads, building and curating datasets and developing data pipelines and processing jobs
• Strong programming skills in Python, Java, or comparable object-oriented language
• Experience working with Databricks or equivalent large-scale data processing platforms
• Demonstrated knowledge of operating within a Public Cloud Provider (e.g. AWS, Microsoft Azure, Google Cloud)
• Experience working with source control systems and CI/CD pipelines
• Strong grasp of computer science fundamentals (data structures, algorithms, design patterns, etc.)
• Strong communication skills, both written and verbal

Skills

• Python
• Java
• Databricks
• AWS
• Microsoft Azure
• Google Cloud
• CI/CD pipelines
• Apache Spark
• Kafka
• Kinesis
• SQS
• NoSQL
• DynamoDB
• Cassandra
• ScyllaDB

Location

• Seattle, WA, USA
• USA - CA - 2450 Broadway
• USA - NY - 7 Hudson Square

Work Type

• Full time

Experience Level

• 3 years of experience

Education Level

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

Salary/Compensations

• $112,000 to $150,100 per year (Seattle, Washington and New York City, New York)
• $106,900 to $143,300 (Santa Monica, CA)

Benefits

• A bonus and/or long-term incentive units may be provided
• Full range of medical, financial, and/or other benefits

About the Company

• 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.
• Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
• Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories.
• 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.