Data Engineer II

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. The Discovery Data 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 and seamless browse 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 Core Data team is central to that mission: we provide the foundational data layer to our Machine Learning models and User Experience APIs to enable the best subscriber experiences and most relevant content to viewer matching possible. Our challenge is to source and provide the highest quality data to feed into our recommendation and browse systems in order to deliver the optimal personalized experience on every request, every time for our hundreds of millions of subscribers around the world. Job Summary: As a Data Engineer II in this role, you’ll apply your passion for data, along with your previous experience working with large-scale datasets, data pipelines, and distributed data systems 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. Responsibilities and Duties of the Role: 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 Required Education, Experience/Skills/Training: Basic Qualifications 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 Preferred Qualifications 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 with NoSQL data stores (e.g. DynamoDB, Cassandra, ScyllaDB, or other) Hands‑on experience using AI and coding assistants to accelerate design and development The hiring range for this position in Seattle, Washington and New York City, New York is $112,000 to $150,100 per year and hiring range for Santa Monica, CA is $106,900 to $143,300. 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. #J-18808-Ljbffr