[Hiring] AI & Data Semantics Lead @Greenfield Talent

Role Description

Our client is seeking an AI & Data Semantics Lead to accelerate enterprise AI initiatives by defining the business meaning behind data used across LLMs, AI models, analytics, and agentic workflows. This role serves as the connective tissue between business stakeholders, data product teams, and technical AI groups — ensuring that data is not only available, but understood.

You will translate complex business concepts into governed semantic assets (business terms, taxonomies, relationships, classifications) that AI systems can safely and accurately consume. This work directly impacts the success of AI use cases, metadata governance, and enterprise data product adoption.

Key Responsibilities

• AI, LLM & Agentic Enablement
  • Define, document, and govern business meaning for data assets used in AI training, inference, and automation.
  • Translate business concepts into structured semantic artifacts consumable by AI systems.
  • Support Responsible AI by ensuring clarity around definitions, ownership, lineage, and usage constraints.
• Business Analysis & Stakeholder Engagement
  • Lead discovery sessions with business partners to extract domain knowledge and convert it into reusable semantic assets.
  • Act as a translator between business leaders, data product owners, engineers, and AI/ML teams.
  • Break down ambiguous business questions into clear data concepts and analytical intent.
• Metadata, Catalog & Taxonomy Development
  • Build and maintain business glossaries, taxonomies, and classification frameworks within an enterprise data catalog.
  • Enrich technical assets with business context, examples, and relationships.
  • Ensure semantic consistency across domains, data products, and AI use cases.
• Data Product & Platform Alignment
  • Align semantic definitions with governed data sources and certified data products.
  • Partner with governance, quality, and lineage teams to ensure metadata completeness and trust.
  • Contribute to standards for AI‑ready metadata and semantic modeling.

Qualifications

• 7+ years in business analysis, data analysis, data product, or related roles.
• Hands‑on experience with enterprise data catalog or metadata platforms (e.g., Alation or similar).
• Demonstrated experience building:
  • Business glossaries
  • Taxonomies / classification models
  • Semantic layers or conceptual data models
• Strong ability to translate technical data assets into clear business language.
• Proven partnership with technical teams (data engineering, analytics, AI/ML).
• Excellent facilitation, documentation, and stakeholder communication skills.