Senior Ontology & Knowledge Graph Architect

Workday, Inc.; Atlanta (GA); Hybrid; USD 160,056 - 216,500; Full time

Job summary

Workday, Inc. is seeking a senior Semantic Engineer to lead ontology and knowledge graph initiatives. You will architect the AI-ready semantic layer and collaborate with governance teams to shape best practices for data semantics across enterprise analytics and BI tools.

The role entails defining standards, managing intake for new requirements, and maintaining comprehensive documentation for the semantic layer while ensuring AI and BI readiness across platforms.

Qualifications

• Master’s degree in Computer Science, Engineering, Information Technology, or related field plus two (2) years of experience in semantic engineering and related areas.
• Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field plus five (5) years of experience in semantic engineering and related areas.

Responsibilities

• Lead the vision, development, implementation, and governance of sophisticated ontologies and knowledge graphs.
• Architect and integrate the semantic layer to serve as an AI-ready knowledge base.
• Develop standards and best practices for knowledge representation and semantic modeling.
• Establish and refine processes for semantic model development and backlog management.
• Collaborate with Data Governance to define policies for semantics governance.
• Partner with analytics engineers and data architects to understand data models in Snowflake and business domains.

Skills

Semantic Engineering

Data Analytics

Data Architecture

Data Engineering

Solution Design

Data Warehousing

Computer Coding

Education

Master’s degree in Computer Science/Engineering/Information Technology

Bachelor’s degree in Computer Science/Engineering/Information Technology

Job description

Workday, Inc. is seeking a senior Semantic Engineer to lead ontology and knowledge graph initiatives. You will architect the AI-ready semantic layer and collaborate with governance teams to shape best practices for data semantics across enterprise analytics and BI tools.

The role entails defining standards, managing intake for new requirements, and maintaining comprehensive documentation for the semantic layer while ensuring AI and BI readiness across platforms.