Data Engineer - Semantics & Domain Models
Data engineer at Chain IQ (a global procurement services firm) in Lisbon, building a shared semantic data layer: canonical entities like suppliers, contracts and risks, domain datasets over a lakehouse, and consistent definitions for analytics, applications and automated workflows.
- Compensation
- Not disclosed
- Location
- Portugal
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Full professional fluency in English (written and spoken)
- 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
Full description
Location: Lisbon, PT
Date: Mar 17, 2026
At Chain IQ, your ideas move fast.
Chain IQ is a global AI-driven Procurement Service Partner, headquartered in Baar, Switzerland, with operations across main centers and 16 offices worldwide. We provide tailored, end-to-end procurement solutions that enable transformation, drive scalability, and deliver substantial reductions in our clients' indirect spend. Our culture is built on innovation, entrepreneurship, ownership, and impact. Here, your voice matters - bold thinking is encouraged, and action follows ambition.
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
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