Beschreibung

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.

Company 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