Lead Data Engineer

Disney Entertainment & ESPN Technology
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 enhance 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:

This role involves building and maintaining content metadata and performance pipelines, as well as collaborating closely with business, analytics, and engineering teams.
You will be responsible for creating and maintaining user-friendly data structures to streamline reporting and monitor key performance indicators across various use-cases, including executive reporting, analytics, data science, and personalization.
These efforts are crucial for effectively supporting organizational business objectives.
The role requires expert knowledge of building scalable, fault-tolerant data processing pipelines to ensure the reliable delivery of data to our partners.
This role is important in ensuring the quality and expediency of our reporting in regards to content metrics.
Responsibilities and Duties of the Role:

Lead the successful design and development of our Data Products and Data Warehouses around Content Performance and Content Engagement data.
Design and develop scalable data warehousing solutions, building ETL pipelines in Big Data environments (cloud, on-prem, hybrid)
Support data pipelines within AWS, Snowflake, Databricks, Spark and Airflow
Help architect data solutions/frameworks and define data models for the underlying data warehouse and data marts
Collaborate with Data Product Managers, Data Architects and Data Engineers to design, implement, and deliver successful data solutions
Maintain detailed documentation of your work and changes to support data quality and data governance
Ensure high operational efficiency and quality of your solutions to meet SLAs and support commitment to our customers (Data Science, Data Analytics teams)
Be an active participant and advocate of agile/scrum practice to ensure health and process improvements for your team
Serve as an advanced resource to other Data Engineers on the team, and mentor and coach more junior members of the team helping to improve their skills, knowledge, and productivity.
Participate in on-call rotations
Basic Qualifications
7+ years of data engineering experience modeling and developing large data pipelines
Strong SQL skills and ability to create queries to extract data and build performant datasets
Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, PySpark) to query and process data
Experience with at least one major MPP or cloud database technology (Snowflake, Redshift, Big Query, Databricks)
Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices
You are a problem solver with strong attention to detail and excellent analytical and communication skills
Preferred Qualifications
In-depth experience with Cloud technologies like AWS (S3, ECS, EMR, EC2, Lambda, etc.)
Solid experience with data integration toolsets (i.e Airflow) and writing and maintaining Data Pipelines
Good Scripting skills, including Python and Bash
Familiar with Scrum and Agile methodologies
7+ years of programming experience using Java/Scala, Python, or similar languages
Required Education
Bachelor's Degree in Computer Science, Information Systems or related field or equivalent work experience

The hiring range for this position in Los Angeles is $149,300 - $200,200 per year and in San Francisco is $163,426 - $219,230 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.
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