Job Summary: On any given day at Disney Entertainment & ESPN Technology, 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: DE&E 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.
Job Summary Data Engineers at Disney are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney, Hulu and ESPN+. They use data to empower decision-makers with information, predictions, and insights that ultimately influence the experiences of millions of users worldwide. Data Engineers in Machine Learning on the team build models, perform statistical analysis, and create visualizations to provide scalable, persistent capability that is iteratively improved through direct interaction with cross-functional business partners.
As a Principal Data Engineer in the Data Platforms team, you will be partnering closely with the Engineering, Architecture, and Product teams to develop models for tackling a multitude of exciting challenges, including asset lifetime value estimation, platform performance, inventory reliability, forecasting, and more. We look for someone with deep analytical and modeling expertise, a proven track record of thought leadership and eagerness to drive impact.
Responsibilities Modeling : Design, build and improve machine learning models. Work end to end from data collection, feature generation and selection, algorithm development, forecasting, visualization and communicating of model results. Collaborate with engineering to productionize models. Drive experimentation to test impact of model-based optimization.
Deep analysis : Develop comprehensive understanding of audience, brand and asset data structures. Mine large data sets to identify opportunities for driving engagement and performance
Visualization of Complex Data sets : Development of prototype solutions, mathematical models, algorithms, and robust analytics leading to actionable insights communicated clearly and visually.
Partnership : Partner closely with stakeholders to identify and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, data visualization, experimentation and data architecture.
Basic Qualifications Bachelors degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
Minimum of 10 years of experience designing, building, deploying data pipelines and applications
Experience building machine learning solutions
Excellent analytical skills, advanced level of statistics knowledge
Strong expertise with Python and libraries such as scikit-learn, SciPy
Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Airflow, Github
Familiarity with designing and analyzing A/B testing and other experiment types
Ability to adapt quickly in a fast-moving environment with shifting priorities
Strong communication skills, for both technical and non-technical audiences
Ability to handle multiple tasks concurrently and in a timely manner, including large and complex ones
Demonstrated leadership experience, including people and project management
Preferred Qualifications Masters degree in Computer Science, Information Systems, Software, Elextrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
5 years of building machine learning solutions
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The hiring range for this position in Santa Monica & Glendale, CA and Bristol, CT is $164.492 to $220,660 per year, in Seattle, WA and New York, NY is $172,282 to $231,110 per year, and in San Francisco, CA is $180,154 to $241,760 per year. 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.
