Lead Data Engineer

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The Disney Decision Science + Integration (DDSI) is a consulting team that supports clients across The Walt Disney Company, including Disney Experiences (Parks & Resorts worldwide, Cruise Line, Consumer Products, etc.), Disney Entertainment (ABC, The Walt Disney Studios, Disney Theatrical, Disney Streaming Services, etc.), ESPN, and Corporate Finance.

We develop, analyze, and execute strategies and improve the value proposition for our Guests, Cast Members, and Shareholders. The team leverages technology, data analytics, optimization, statistical and econometric modeling to explore opportunities, shape business decisions and drive business value.

What You Will Do

You will be responsible for planning and leading research and development related to advanced analytic data solutions, leveraging GenAI. You will work with business and technology leaders to understand scope and requirements, business needs, and data from across the Disney company in order to design and deliver the data pipelines necessary for our solutions.

You will partner with the Decision Science Products, Decision Science, and client teams on critical projects. Other activities include planning, estimating, design, development, testing, production rollout and sustainment activities. You will also need to consult and collaborate with project team members, lead design reviews, do hands-on development, and communicate with colleagues and leaders.

Required Qualifications & Skills

• 7+ years overall experience in a data engineering development capacity using a multiple environments (Dev, QA, Prod, etc.) and DevOps procedures for code deployment / promotion
• Experience with a variety of GenAI models, tools, and concepts
• 3+ years using, designing and building relational databases (preferably Snowflake or PostgreSQL)
• 3+ years of experience leading and deploying code using a source control product such as GitLab / GitHub
• 2+ years of experience with job scheduling software like Apache Airflow, Amazon MWAA, GitLab Runners or UC4
• Multiple years of experience with ELT / ETL data pipeline development and maintenance
• Multiple years of shown experience and expertise using SQL and Python
• Experience using containerization technologies such as Docker or Kubernetes
• Knowledgeable on cloud architecture and product offerings, preferably AWS
• Understanding of Knowledge Graphs, Data Mesh, and other data sharing platforms
• Experience translating project scope and high-level requirements into technical data engineering tasks
• Experience defining solutions to sophisticated data engineering problems in support of advanced analytic processes
• Experience collaborating with multiple project teams in a fast-paced environment
• Experience with defining and estimating level-of-effort data engineering activities
• Experience with project and sprint planning
• Ability to communicate technical concepts and solutions to non-technical team members
• Experience designing and building data structures to support requirements

Preferred Qualifications

Education

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