Lead Data and Ontology Engineer

The Walt Disney Company

Lead Data and Ontology Engineer at Disney implementing graph technologies and semantic modeling for enterprise decision-making. Collaborate across teams to enhance business value delivery through data architecture.

Posted 7/20/2026full-timeLake Buena Vista • California, Florida, New York, Washington • 🇺🇸 United StatesSenior💰 $148,300 - $218,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in ontology modeling, semantic technologies, and graph databases to design and implement enterprise ontologies and knowledge graphs that align with business objectives. Proficient in data governance, security models, and collaboration with cross-functional teams to drive AI integration and data access strategies.

Highest-signal resume keywords

Ontology Modeling (OWL, RDF, SKOS, SHACL)Graph Technologies (Neo4j, Neptune)Vector DatabasesData Governance and Security (RBAC/ABAC)Programming Skills (Python, SPARQL, Cypher, GraphQL, SQL)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Ontology ModelingGraph TechnologiesVector DatabasesData CatalogsSemantic Metadata ManagementFederated Data ArchitecturesProgramming (Python, SPARQL, Cypher, GraphQL, SQL)Data GovernanceSecurity ModelsCloud Services (AWS)

Soft Skills

Excellent Communication Skills

Tools & Technologies

Neo4jNeptunePostgreSQLSnowflakeMongoDBS3KafkaAWS

Industry Keywords

Data EngineeringData ArchitectureSemantic TechnologiesKnowledge EngineeringEnterprise Ontologies

Tech Stack

Tools & technologies

AWSCloudGraphQLKafkaMongoDBNeo4jPostgresPythonSQL

About the role

Key responsibilities & impact

Lead the design, development, and governance of enterprise ontologies, semantic layers, and knowledge graphs.
Combine deep semantic modeling expertise with hands-on implementation of graph technologies, vector databases, and federated data architectures.
Design and build enterprise ontologies and semantic models that align business objectives with technical implementation.
Lead the creation and maintenance of semantic layer graphs, knowledge graphs, and entity graphs.
Develop and implement strategies for using vector databases and graph databases to enable powerful LLM-augmented search and reasoning.
Partner with data engineering, AI, and business teams to translate business goals into ontological models.
Contribute to the development of a unified data access layer that supports querying across diverse data sources.
Implement and enforce enterprise security models through the ontology and semantic layer.
Collaborate on AI integration initiatives, including building ontology-driven agents.
Establish ontology governance processes and contribute to the internal Data Marketplace.

Requirements

What you’ll need

7+ years of experience in data engineering, data architecture, semantic technologies, knowledge engineering, or related fields with a strong technical implementation background.
Deep expertise in ontology modeling (OWL, RDF, SKOS, SHACL) and graph technologies.
Strong understanding of the differences between semantic layer graphs, knowledge graphs, and entity graphs and when to apply each.
Hands-on experience with graph databases (Neo4j, Neptune, etc.) and vector databases for semantic search and LLM integration.
Proficiency in designing and implementing Data Catalogs and semantic metadata management solutions.
Experience building solutions on top of federated data architectures involving relational (PostgreSQL, Snowflake), document (MongoDB), object (S3), and streaming (Kafka) systems.
Demonstrated ability to translate complex business goals into ontological designs that accelerate delivery of business value.
Strong programming skills, particularly Python, SPARQL, Cypher, GraphQL, and SQL.
Experience with modern data platforms, cloud services (AWS preferred), and infrastructure-as-code practices.
Solid understanding of data governance, security (RBAC/ABAC, dynamic masking), and compliance in enterprise environments.
Excellent communication skills with the ability to bridge business stakeholders and technical teams.

Benefits

Comp & perks

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.