Description
Designs and delivers the data and AI architecture that powers next-generation analytics
Deep technical expertise with strategic influence to build a scalable, intelligent data ecosystem for the organization.
AI & Data Architect SpecialistCompany based in Geneva
Description
Data Architecture & Strategy
- Develop and maintain enterprise-level data models and architectural blueprints
- Define standards for scalable, interoperable, and future-proof data architecture
- Recommend technologies for semantic search, knowledge representation, and AI-driven data services
AI & Data Intelligence Enablement
- Assess and integrate advanced data technologies (vector stores, graph databases, embeddings, retrieval pipelines)
- Contribute to the design of AI-enabled products such as knowledge assistants and document intelligence tools
- Promote practices that optimize data assets for machine learning and LLM applications
Collaboration & Implementation
- Serve as the main point of contact for data initiatives (Data Hub, Self-Service Analytics, RAG-based applications)
- Support the evolution of the Data Warehouse and Data Hub to align with business priorities
- Collaborate with development teams to ensure alignment with architectural standards
Governance & Compliance
- Define and enforce governance frameworks including glossary, cataloging, and metadata management
- Ensure data consistency, lineage tracking, and proper documentation across platforms
- Work with security and legal stakeholders to maintain compliance with regulatory requirements
Continuous Improvement
Stay informed on emerging technologies in data and AI
Lead initiatives to improve data quality, accessibility, and readiness for AI workloads
Profile
- Strong background in data architecture or data engineering, with exposure to AI-focused systems
- Hands-on experience with cloud-based data platforms (AWS, Oracle Cloud Infrastructure)
- Knowledge of vector databases (, Pinecone, FAISS) and graph databases (, Neo4j, AWS Neptune)
- Familiarity with data governance frameworks (, DAMA-DMBOK) and metadata standards
- Understanding of ML pipelines and LLM integrations (RAG, semantic search)
- Proficiency in SQL, Python, and modern ETL/ELT approaches
- Awareness of emerging AI regulations (, EU AI Act)
- Strong leadership, communication, and project coordination skills
- Ability to translate complex technical concepts into clear business value
- Curious, strategic mindset with a strong drive toward innovation
Job Offer
- International environment
- Attractive package
