* International environment
* Data Warehouse and Governance
About Our Client
Our client is located in Geneva
Job Description
Data architecture and technology
* define, maintain and document conceptual and logical data models for the data ecosystem in close collaboration with Enterprise and Data architect
* define, implement and monitor compliance to data architecture principles, ensuring consistency, scalability, and interoperability across systems
* identify and recommend technologies for semantic search, knowledge graphs, and AI-enhanced data access AI and data intelligence enablement
* evaluate and implement AI-oriented data technologies, including vector databases, graph databases, embeddings, and retrieval pipelines
* work with data team to scale and integrate new technologies into the data architecture
* contribute to the design of AI enabled applications (e.g., content discovery, document intelligence, knowledge assistants, etc.)
* promote best practices for data preparation, enrichment, and optimization for AI models
Collaboration with all IT teams (Digital Workplace, Back Office Solutions and Data, and Customer Solutions and Infrastructure)
* Specialist data team and act as the IT SPOC for implementation of data related initiatives (DataHub, Selfservice Analytics, RAG based application, AI Based initiatives etc.)
* monitor and guide the evolution of the Data Warehouse and Data Hub to ensure alignment with organizational needs and technological advancements
* partner with development teams (internal or external) to support and guarantee evolution of data models
* sign off IT solution design reviews to guarantee compliance with established data architecture and data models
Governance and quality
* define and enforce compliance with data governance (Data Glossary, Data Catalog, etc..), and Metadata Management Standards
* ensure data consistency, traceability and lineage, and documentation across systems
* collaborate with the IT Information Security Officer and the Legal and compliance team to maintain data protection standards and data to maintain data protection standards
Best practices
* be familiar with best practices in related processes and areas of work
* carry out work in alignment with strategic objectives and rules to deliver optimal service to both internal and external stakeholders
The Successful Applicant
Strong background in data architecture or data engineering, ideally with exposure to both traditional and AIenhanced data systems.
Hands-on experience with cloud-based data platforms (AWS and OCI - Oracle Cloud Infrastructure) and modern data stack components.
Knowledge of vector databases (e.g., Pinecone, FAISS, Azure Cognitive Search) and graph databases (e.g., Neo4j, AWS Neptune, Oracle Graph).
Knowledge and practice of a data management framework (DAMA-DMBOK).
Knowledge of and understanding of AI-related regulations (e.g., EU AI Act).
Familiarity with data modeling tools, conceptual model design, and metadata management.
Understanding of machine learning pipelines and LLM integrations (embedding retrieval, RAG, semantic search).
Proficiency in SQL, Python, and modern ETL/ELT frameworks.
Solid working knowledge of relevant digital tools, curious about, able to learn, assimilate and understand the
impacts of current and future technologies.
Demonstrate strong project management and leadership skills, with the ability to plan, coordinate, and lead
the implementation of data initiatives, manage vendors and external partners, and ensure alignment with
strategic objectives, timelines, and quality standards.
What's on Offer
Attractive environment
Flexible Hours
2 days of home office per week.
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