Lead Data and Ontology Engineer

Jobtailor; California (MO); On-site; USD 140,000 - 210,000; Full time

Job summary

Jobtailor seeks an experienced data engineer to lead the design, governance, and implementation of enterprise ontologies, semantic layers, and knowledge graphs.

You will combine semantic modeling with hands-on graph and vector database work (Neo4j, Neptune, AWS) to power AI‑augmented search, while aligning business goals with technical solutions and ensuring robust security and data governance.

Qualifications

• 7+ years of experience in data engineering, data architecture, semantic technologies, knowledge engineering, or related fields with a strong technical implementation background.

Responsibilities

• Lead 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.

Skills

Ontology Modeling

Graph Technologies

Vector Databases

Data Governance

Security Models

Programming: Python

SPARQL

Cypher

Tools

Neo4j

Neptune

PostgreSQL

Snowflake

MongoDB

S3

Kafka

AWS

Job description

• 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

• 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.

Core Competencies

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 Databases


• Data Governance and Security (RBAC/ABAC)


• Programming Skills (Python, SPARQL, Cypher, GraphQL, SQL)

ATS Optimization Keywords

Hard Skills

• Ontology Modeling


• Graph Technologies


• Vector Databases


• Data Catalogs


• Semantic Metadata Management


• Federated Data Architectures


• Programming (Python, SPARQL, Cypher, GraphQL, SQL)


• Data Governance


• Security Models


• Cloud Services (AWS)

Soft Skills

• Excellent Communication Skills

Industry Keywords

• Data Engineering


• Data Architecture


• Semantic Technologies


• Knowledge Engineering


• Enterprise Ontologies

Tools & Technologies

• Neo4j


• Neptune


• PostgreSQL


• Snowflake


• MongoDB


• S3


• Kafka


• AWS