Senior Data Specialist

vor 3 Wochen

Genf, Schweiz Michael Page International (Switzerland) SA Vollzeit

About Our Client Company based in Geneva Job Description Data Architecture Define and implement the enterprise data architecture vision across on-prem and cloud platforms, evolving beyond traditional Oracle-based setups. Transform current data teams by promoting modernization, automation, and reduced custom coding in favor of scalable, industrialized solutions. Guide the transition toward externalized development (nearshoring/offshoring) and oversee delivery quality, alignment, and compliance. AI & Data Intelligence Enablement Design and drive AI-enablement frameworks, including semantic search, LLM integration, RAG pipelines, knowledge assistants, and document intelligence. Introduce and pilot emerging AI technologies (vector stores, graph databases, embeddings, retrieval frameworks) with hands‑on prototype validation. Collaboration & Implementation Serve as the main point of contact for data initiatives (Data Hub, Self‑Service Analytics, RAG‑based applications) Coordinate with nearshore external development teams, validate deliverables, and oversee adherence to architectural standards. Communicate effectively across business, technical, and leadership stakeholders to translate concepts into actionable value. Governance & Compliance Define and enforce governance frameworks including glossary, cataloging, and metadata management Ensure consistency across data assets regardless of platform: Oracle, Azure, AWS, Power BI, or other cloud ecosystems. Act as key liaison with security, legal, and compliance teams to align with evolving data and AI regulations. Continuous Improvement Stay informed on emerging technologies in data and AI Lead initiatives to improve data quality, accessibility, and readiness for AI workloads The Successful Applicant Strong background in data architecture or data engineering, with proven experience in data modernization and exposure to AI‑focused systems Hands‑on experience with cloud‑based data platforms (AWS, Oracle Cloud Infrastructure) Very good understanding of data warehouse concepts, data governance, metadata management, and stewardship practices. Exposure to AI technologies: LLM integration, embeddings, RAG, semantic search, knowledge graph, vector databases (Neo4j, Pinecone, FAISS, etc.) Hands‑on experience in at least one AI‑related pilot or proof of concept (not just theoretical). Experience managing or supervising external development partners (nearshore/offshore), including quality, delivery, and alignment. Strong communication, mentoring ability, and capability to drive change within technical teams. Strategic mindset, curiosity, and strong desire to innovate and build scalable data and AI capabilities for the future. What's on Offer International environment Attractive package #J-18808-Ljbffr

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