Manager, Data Engineering

Manager, Data Engineering

The Disney Decision Science and Integration (DDSI) team leverages advanced technologies, Gen AI, data analytics, and scientific approaches such as optimization, and statistical modeling to build innovative tools that shape business decisions across The Walt Disney Company. We support Disney Entertainment (ABC, The Walt Disney Studios, Disney+, Hulu), ESPN, Disney Experiences (Theme Parks, Cruise Line, Consumer Products, DVC), Corporate Finance, and others with strategic applications that enable data-driven decision-making and drive business value.

This is not a remote role. This team works in office.

What You Will Do

Data is the foundation of everything DDSI builds, and our Data Engineering team is the engine behind it—responsible for acquiring, processing, and delivering the data that powers projects across the organization. As Manager, Data Engineering, you will lead a talented team through the research, development, and delivery of advanced, GenAI-powered analytic data solutions. Your team's work spans the full data lifecycle: acquiring and validating data, designing and implementing ETL/ELT pipelines, architecting databases and knowledge graphs, integrating with enterprise data platforms, and delivering ad-hoc analytics. You will also help shape the future of the DDSI Data Engineering organization—championing generative AI adoption, introducing advanced tooling, and refining the processes that keep the team moving fast. In this role, your team will harness generative AI development tools to work efficiently and will design, build, and operate the intelligent, agentic systems that power large-scale, data-intensive applications.

You will partner closely with business and technology leaders across The Walt Disney Company to understand their goals and data, translating that insight into a strategic development roadmap. Day to day, you will scope and estimate work, direct assignments across the team, and ensure consistent design patterns and principles across a diverse portfolio of projects—all while clearing the technical, business, and organizational roadblocks that stand in your team's way. Just as importantly, you will grow the people who make this work possible: hiring exceptional talent, setting career goals, delivering meaningful performance feedback, and partnering with senior leadership to keep the team well-staffed and set up to succeed.

The ideal candidate has not only strong Data Engineering experience, but also a diverse background across multiple technology areas which might include Generative AI, Data Warehousing, Application Development, Architecture, Networking and/or Infrastructure.

Required Qualifications & Skills

• 8+ years of experience in technology roles, ideally spanning data engineering, software engineering, and/or architecture
• 2+ years of experience leading and developing technology teams in a management capacity
• Proven ability to identify, evaluate, and implement new data platforms, tools, and solutions to meet emerging business needs
• Working knowledge of generative AI concepts—including LLMs, RAG, knowledge graphs, and agents—and hands-on experience applying GenAI tools to develop and deploy data solutions
• Ability to bridge the business and technical worlds, applying strong business and domain knowledge
• Proven ability to drive comprehensive solutions from scoping through implementation while meeting deadlines and balancing competing priorities
• Excellent communication skills, with the ability to engage effectively at all levels of the organization
• Experience managing large-scale data platforms supporting one or more applications
• Experience working with both structured and unstructured data
• Experience designing, building, and maintaining ETL/ELT data pipelines
• Strong command of relational database design, with proficiency in tools such as PostgreSQL, Snowflake, or Aurora
• Deep understanding of the distinctions and appropriate uses of application databases, data warehouses, and data lakes
• Broad experience across data, application, infrastructure, and architecture technologies
• Experience with modern cloud-based tools, both licensed and open-source, preferably AWS
• Experience managing and deploying code using source control tools such as GitLab or GitHub
• Experience with containerization technologies such as Docker and Kubernetes
• Passion for driving standards, processes, and consistency, including designing reusable tools that benefit projects across the department

Desired Qualifications:

• Hands-on experience using GenAI models and related tools
• Experience building agents and creating agentic orchestration
• Proven experience defining and leading strategic initiatives
• Prior experience with Theme Park, Hospitality, or Entertainment industries
• Prior experience in a DBA capacity and with performance tuning
• Knowledgeable with Architecture Principles and Design
• Experience leveraging Snowflake in an OLTP and OLAP capacity
• Multiple years of experience with Python and SQL
• Familiarity with data streaming and batch data processing
• Knowledgeable knowing how to leverage job scheduling software like Apache Airflow
• Involved in driving standard practices around data engineering software development processes

Education:

Bachelor's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study and/or equivalent work experience

Preferred - Master's degree - Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study and/or equivalent work experience

The hiring range for this position in Orlando, FL $163,400 to $219,100 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.