The Disney Decision Science and Integration (DDSI) team leverages advanced technologies, 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), and Corporate Finance with strategic applications that enable data-driven decision-making. 

What You Will Do

The Data Engineering team leads the acquisition and processing of all data needed for projects across DDSI.  A key initiative for this role will be to support Disney’s enterprise Data Unification initiative by building and maintaining the technical foundations that enable seamless access to federated data across the enterprise. You will work closely with the Ontology/Semantic Librarian, data science, and business teams to implement and optimize unified data access patterns, federated querying capabilities, and semantic integration solutions.

You will focus on enabling efficient discovery and querying of heterogeneous data sources through semantic layers, knowledge graphs, and GraphQL interfaces. This includes building and enhancing components that allow users and AI agents to query across a variety of data sources. You will also implement data pipelines and integration processes as needed to support data unification, semantic modeling, and AI use cases.  In addition to strong technical capabilities, the role is responsible for developing an understanding of the business domain and processes, then applying that knowledge to the assigned deliverables.

Basic Qualifications

• 3+ years of experience in data engineering, data platform development, or backend engineering roles

• Strong experience implementing federated data access solutions and unified query layers

• Proficiency with GraphQL for building semantic data interfaces and APIs

• Hands-on experience with cloud data platforms such as Snowflake, Databricks, PostgreSQL, or S3

• Proficiency using Python and SQL for data integration and transformation tasks

• Experience working with heterogeneous and federated data sources, including streaming platforms like Kafka

• Familiarity with semantic technologies, knowledge graphs, or ontology-driven architectures

• Familiarity with vector databases and/or graph databases (e.g., Qdrant, Neo4j, or Amazon Neptune)

• Experience building or maintaining data pipelines and integration processes to support semantic and AI use cases

• Understanding of RAG architectures, embeddings, and LLM-augmented data access patterns

• Experience working in multi-environment setups (Dev, QA, Prod) with DevOps practices and source control (Git)

• Understanding of data modeling, query optimization, and API development

Desired Qualifications

• Hands-on experience with vector databases or graph databases

• Experience with semantic layers, knowledge graphs, or ontology-driven data architectures

• Experience working with federated query engines (e.g., Trino/Presto, Apache Iceberg)

• Experience with data orchestration tools such as Apache Airflow or Apache Flink

• Experience working with GenAI APIs or frameworks (e.g., OpenAI, LangChain, AWS Bedrock)

• Knowledgeable on cloud architecture and product offerings, preferably AWS

• Experience leveraging containerization technologies such as Docker or Kubernetes

• Demonstrated proficiency with API development

• Business knowledge with media, entertainment, or hospitality

Required 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 Education

• Master's degree in 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 Lake Buena Vista, FL is $101,800 to $136,500 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.