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# Data Engineer

- **Company:** The Walt Disney Company
- **Location:** Orlando, FL, United States
- **Experience:** Experienced
- **Salary:** $101,800.0 - $136,500.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Cloud Engineering, Information Systems, Data Architecture, Information Engineering, Data Infrastructure, Data Integration, Data Security, DevOps, Graph Database, Python (Programming Language), PostgreSQL, Neo4j, Query Optimization, Cloud Services, SQL Databases, Data Streaming, Data Server Interface, Large Language Models, Snowflake, Git, Data Layers, Containerization, Kubernetes, Information Technology, Apache Flink, Apache Kafka, Graphql, Presto, Api Design, Software Version Control, Data Pipelines, Docker, Databricks
- **Published:** August 24, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3363837757&tx=KR3131FFP&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 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

#DISNEYTECH

## Description

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.


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