Global Data Ontology Analyst

About the role

Do you enjoy turning business knowledge into structured, reusable data assets? As a Global Data Ontology Analyst you will define and maintain IFF’s enterprise business ontology, ensuring consistent context for data concepts, relationships, and rules across systems, reporting platforms and AI solutions.

Key responsibilities

• Develop and maintain enterprise data ontologies, semantic models, business vocabularies and conceptual data models.
• Define business entities, attributes, relationships and rules that enable enterprise‑wide data consistency.
• Partner with business teams to document and standardise concepts such as Customer, Product, Supplier, Formula, Material, Plant and Sales Organization.
• Collaborate with Data Owners and Data Stewards to align ontologies with glossaries, master‑data standards and governance policies.
• Maintain metadata frameworks, taxonomies, business glossaries and data dictionaries.
• Review business processes and data flows to identify opportunities for ontology development and semantic standardisation.
• Coordinate ontology lifecycle governance, including change management, versioning, stewardship and approval workflows.
• Work with data architects and solution teams to align semantic models with data‑architecture initiatives.
• Promote adoption of semantic standards through documentation, training and stakeholder engagement, linking AI, reporting and insight initiatives to consistent definitions.

Required profile

• Bachelor’s degree in Information Management, Data Governance, Computer Science, Business Reporting, Information Systems, Knowledge Management or a related field.
• 2‑5 years of experience in Data Governance, Metadata Management, Master Data Management, Data Architecture or related disciplines.
• Strong knowledge of data‑governance practices, metadata management, business glossaries, master‑data management and data‑quality concepts.
• Experience developing conceptual or semantic data models.
• Familiarity with ontology concepts, taxonomies, semantic models, knowledge graphs and enterprise information architecture.
• Understanding of DAMA‑DMBOK and metadata‑management best practices.

Required skills