Lead Data architect

THE ROLE

We are seeking a Lead Data Architect to secure the urbanization of our data platform and industrialize the delivery of high quality data products. Your primary mission is to design and govern a coherent, scalable data architecture that accelerates time to value for Analytics and AI use cases by ensuring that reliable and well‑certified data are delivered through a robust end‑to‑end process.

As a Lead, you will not only define the target data architecture and standards but also manage and coordinate a team of Data Architects (initially external resources). You will monitor their work, ensure consistency across domains, and build a strong data architecture community and capabilities over time.

WHAT ARE YOU GOING TO DO?

1. Leadership & Team Management (Data Architects)
   • Promote Data Architecture strategy & vision
   • Lead and coordinate a pool of Data Architects (primarily external partners)
   • Plan, prioritize, and allocate architecture work across initiatives and domains to maximize impact and coherence
   • Ensure consistency of architectural approaches, models, and deliverables across all Data Architects
   • Provide day‑to‑day guidance, coaching, and feedback to Data Architects to develop their expertise and align them with Group standards
   • Define and monitor expectations and deliverables
   • Build and ensure proper animation of the Data Architecture community (rituals, best practice sharing, documentation, training)
   • Ensure alignment with Group data strategy and Enterprise architecture principles
2. Data Architecture
   • Update and maintain the target data platform architecture to build the Single Source of Truth and support current and future Analytics & AI needs
   • Urbanize the data landscape by structuring domains, data products, and shared capabilities
   • Enforce reference architectures, design patterns, and standards across data domains and platforms (e.g., data lake, enterprise data warehouse, data domain factories)
3. Data Modeling
   • Define modeling standards, patterns, and best practices (conceptual and logical models)
   • Lead and review the design of complex data models across domains (analytical, Data Vault, dimensional/star schemas, semantic models)
   • Guarantee semantic consistency, normalization where needed, and optimal denormalization for performance and usability
   • Ensure data models are robust, evolutive, and designed for reusability across multiple use cases and data products
   • Coach and challenge Data Architects and Data Engineers on modeling decisions to safeguard data quality, integrity, and long‑term maintainability
4. Data Product Strategy, Lifecycle & Certification
   • Define the data product blueprint (contract, SLAs, quality criteria, ownership, classification, metadata, documentation)
   • Design and continuously improve the delivery process for data products (methodology, templates, gates, design authority and governance)
   • Lead and standardize the end‑to‑end data product lifecycle process: framing, design, build, test, certification, deployment, and evolution
   • Work with business stakeholders and Analytics/AI teams to translate use case requirements into sustainable, reusable data products
   • Ensure traceability and lineage from source systems to data products, enabling trust and explainability
   • Implement a robust data product certification framework (quality checks, UAT, run organization, deliverable sign‑offs)
5. Cross Functional Leadership & Collaboration
   • Act as the architectural lead and primary point of contact for data platform and data product architecture topics
   • Collaborate closely with Business stakeholders, Enterprise & Solution Architects, Data Engineers, Data Scientists, AI/ML engineers, and Data Governance & Data Management experts
   • Influence and align technical and business stakeholders around a common data architecture vision and roadmap
6. Technology Watch & Continuous Improvement
   • Evangelize modern data architecture, data product thinking, and platform capabilities across the organization
   • Evaluate and recommend technologies, tools, and architectural approaches that accelerate data product delivery and improve reliability

WHO ARE WE LOOKING FOR?

• 12+ years of professional experience in data related roles, including significant experience as a Data Architect and several years in a lead/principal capacity
• Strong communication, influencing, and leadership skills, with the ability to align technical and business stakeholders around a common data vision
• Experience managing or coordinating external partners/consultants, ideally in a data or architecture context
• Excellent analytical and problem‑solving skills, with a strong delivery and outcome orientation
• Proven track record in data modeling excellence, mastery of conceptual, logical modeling, data warehousing and analytics modeling (e.g., dimensional/star schemas, 3NF), solid experience with Data Vault 2.0 methodology, and ability to challenge and optimize existing models for performance, scalability, and maintainability
• Deep expertise in ETL/ELT processes and integration patterns
• Strong experience with cloud‑based data solutions (e.g., AWS, Google Cloud, Snowflake) and modern data platform components
• Solid understanding of Analytics and AI/ML concepts
• Experience with BI/Analytics & Exploration tools (e.g., Qlik, PowerBI, Sigma)
• Understanding of data governance and data management practices, including knowledge of tools such as Data catalog, Data quality & observability, Master Data Management; demonstrated ability to define and run data architectural standards, review boards, or design authorities.