On any given day at Disney Entertainment & ESPN Product & Technology (DEEP&T), we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.
A few reasons why we think you’d love working for Disney Entertainment & ESPN Technology
Building the future of Disney’s media business: DEEP&T Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.
Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.
Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.
The Product & Data Engineering team is responsible for end to end development for Disney’s world-class consumer-facing products, including streaming platforms Disney+, Hulu, and ESPN+, and digital products & experiences across ESPN, Marvel, Disney Studios, NatGeo, and ABC News. The team drives innovation at scale for millions of consumers around the world across Apple, Android, Smart TVs, game consoles, and the web, with our platforms powering core experiences like personalization, search, messaging and data.
This role involves building and maintaining our Identity and Device Data products. These products serve as a comprehensive source of truth for customer identifiers and their devices. The role requires expert knowledge of building scalable, fault-tolerant data processing pipelines and backend to ensure the reliable delivery of both real-time and batch data.
Build and maintain product-driven initiatives to improve and expand Identity and Device data product offerings
Enhance/improve the underlying codebase to be extensible, reusable, and maintainable
Enhance/redesign existing data models with input from Architecture in order to modernize products and/or improve performance and efficiency
Promote and support Agile methodologies such as Scrum, Kanban, and Scrumban by actively participating in regular ceremonies such as stand-up, retrospectives and sprint planning.
Collaborate with your squad, Product Managers, Designers, QA, Operations, and other stakeholders to understand requirements and articulate technical decisions and outcomes.
Participate in on-call support
Serve as an advanced resource to other Data Engineers on the team, and mentor and coach junior members of the team helping to improve their skills, knowledge, and productivity.
Participate in code reviews and problem-solving.
Bachelor's degree in Computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
7+ years of related big data engineering experience modeling and developing large data pipelines
Deep hands-on experience with distributed systems such as Hadoop or Databricks compute using tools/libraries such as Spark, Presto, Hive to query and process large datasets at the petabyte level.
Strong Python, Scala and SQL skills processing big datasets
Strong Experience with at least one major MPP or cloud database technology (Snowflake, Redshift, Big Query, Databricks)
Deep understanding of Data Modeling techniques and Data Warehousing standard methodologies and practices
Operational experience in multi-system/services production environment as lead data engineer and point-of-contact / SME
Strong problem solving skills with strong attention to detail and excellent analytical and communication skills
Solid experience with data integration and orchestration toolsets (e.g. Airflow), CI/CD
Solid experience with AWS S3
Demonstrated ability with cloud infrastructure technologies, including Terraform
Additional Information
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