We are moving away from fragmented metrics and dashboard-specific logic toward a shared, semantic data foundation. This role focuses on defining what data means across the platform and ensuring consistency for applications, analytics and automated workflows. 

This is a hands-on role that sits close to product and engineering. You turn complex, real-world procurement processes into structured, understandable data models that scale. 

Responsibilities 

• Define and maintain canonical domain entities such as suppliers, contracts, risks and obligations 

• Build semantic datasets that reflect real workflows and business logic 

• Model relationships, hierarchies and time-based changes explicitly 

• Ensure consistent definitions across products, analytics and automation 

• Design patterns for linking documents to structured entities 

• Support gradual evolution toward graph-based and retrieval-driven use cases 

• Collaborate with Product, AI and Engineering teams to align data with system behavior 

• Help remove duplicated and inconsistent logic from dashboards and downstream tools 

What you will work with 

• Semantic layers built on top of lakehouse data 

• Domain-oriented datasets and views 

• Relationship-aware modelling patterns 

• Metadata, classification and descriptive attributes 

• Consumers including applications, analytics and automated workflows 

Requirements 

• Full professional fluency in English (written and spoken) is mandatory

• Experience with semantic or analytics engineering concepts 

• Strong understanding of domain modelling and data relationships 

• Ability to translate complex business processes into structured data 

• Comfort collaborating across product and engineering teams 

• Clear communication and attention to consistency and correctness 

• Interest in enabling automation and reasoning through better data design