Lead Data Engineer

$149,300 - $200,200/Yr

Disney - Santa Monica, CA

Full-time - Mid Level

Santa Monica, CA

Motion Picture and Sound Recording Industries

About the position

The role at Disney Entertainment & ESPN Technology focuses on building and maintaining the Audience Manager Platform (AMP), a centralized data platform that captures and processes consumer behavior across various channels. This position is integral to enhancing Disney's media, advertising, and distribution businesses by ensuring reliable delivery of audience data through scalable and fault-tolerant data processing pipelines. The team is responsible for developing innovative consumer-facing products and experiences across multiple platforms, including Disney+, Hulu, and ESPN+.

Responsibilities

• Build and maintain product-driven initiatives to improve and expand the Unified Messaging Platform.
• Enhance/improve the underlying codebase to be extensible, reusable, and maintainable.
• 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 more junior members of the team.

Requirements

• Bachelor's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
• Minimum 7 years of related big data engineering experience modeling and developing large data pipelines.
• Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, PySpark) to query and process data.
• Strong Python and SQL skills processing big datasets.
• 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.
• Problem solver with strong attention to detail and excellent analytical and communication skills.

Nice-to-haves

• In-depth experience with Cloud technologies like AWS (S3, ECS, EMR, EC2, Lambda, etc.).
• Solid experience with data integration toolsets (i.e Airflow), CI/CD.
• Familiar with Scrum and Agile methodologies.

Benefits

• Medical insurance coverage
• Financial benefits including bonuses and long-term incentive units
• Flexible working arrangements
• Opportunities for professional development and growth