AI and Data Architect Specialist

Michael Page
Geneva, Switzerland
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Geneva, Switzerland

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Azure
Encodings
Computer Security
Databases
Data Architecture
Data Cleansing
Information Engineering
Data Governance
Data Hub
ETL
Data Security
Dataspaces
Data Systems
Data Warehousing
Graph Database
Data Intelligence
Interoperability
Python
Logical Data Models
Meta-Data Management
Neo4j
Oracle Applications
Software Architecture
Search Technologies
Software Engineering
SQL Databases
Cloud Platform System
Large Language Models
Data Management
Machine Learning Operations
Oracle Cloud Infrastructure

Job description

Our client, an international organization based in Geneva, is looking for an AI & Data Architecture Specialist to design and implement a modern, scalable, and intelligent Data & AI ecosystem. You will play a key role in the digital transformation by defining the architecture, standards, and best practices that unlock the value of data and advanced AI technologies (RAG, LLMs, vector databases, graph databases, etc.)., * 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, 4.4

  • Salary and benefits 4.0

  • Career opportunities 4.4

  • Working atmosphere 4.4

Based on 31 reviews http://Michaelpage.ch

Categories:

IT / Telecommunications, Data Warehouse / Business Intelligence / CRM, Consulting / Management / Project Management, Business- / Requirement Analyst / Process Management, Database specialist / Architecture, Software Development / Software Architecture

Requirements

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.

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