Data Engineer

Data EngineerThe 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.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 Qualifications3+ years of experience in data engineering, data platform development, or backend engineering rolesStrong experience implementing federated data access solutions and unified query layersProficiency with GraphQL for building semantic data interfaces and APIsHands-on experience with cloud data platforms such as Snowflake, Databricks, PostgreSQL, or S3Proficiency using Python and SQL for data integration and transformation tasksExperience working with heterogeneous and federated data sources, including streaming platforms like KafkaFamiliarity with semantic technologies, knowledge graphs, or ontology-driven architecturesFamiliarity 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 casesUnderstanding of RAG architectures, embeddings, and LLM-augmented data access patternsExperience working in multi-environment setups (Dev, QA, Prod) with DevOps practices and source control (Git)Understanding of data modeling, query optimization, and API developmentDesired QualificationsHands-on experience with vector databases or graph databasesExperience with semantic layers, knowledge graphs, or ontology-driven data architecturesExperience working with federated query engines (e.g., Trino/Presto, Apache Iceberg)Experience with data orchestration tools such as Apache Airflow or Apache FlinkExperience working with GenAI APIs or frameworks (e.g., OpenAI, LangChain, AWS Bedrock)Knowledgeable on cloud architecture and product offerings, preferably AWSExperience leveraging containerization technologies such as Docker or KubernetesDemonstrated proficiency with API developmentBusiness knowledge with media, entertainment, or hospitalityRequired EducationBachelor's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study and/or equivalent work experiencePreferred EducationMaster's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study and/or equivalent work experience