Data Engineer II

Data Engineer II

Job
Location Seattle, Washington, United States / Santa Monica, California, United States / New York, New York, United States
Business Disney Entertainment and ESPN Product & Technology
Date posted
Jul. 10, 2026

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, working 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.

The Discovery Data team builds systems that provide tailored experiences to viewers across our streaming products. The Core Data team provides the foundational data layer to our machine‑learning models and user‑experience APIs, enabling the best subscriber experiences and the most relevant content to viewer matching possible. Our challenge is to source and provide the highest quality data to feed into recommendation and browsing systems for hundreds of millions of subscribers worldwide.

• 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 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.

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 a comparable object‑oriented language.
• Experience working with Databricks or an equivalent large‑scale data processing platform.
• 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 No
  
  SQL 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 the hiring range for Santa Monica, CA is $106,900 to $143,300. The base pay offered will take into account internal equity and 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…