ID: 577973
Location:
Marseille, FR
Lead Data architect
Led by Rodolphe Saadé, the CMA CGM Group, a global leader in shipping and logistics, serves more than 420 ports around the world on five continents. With its subsidiary CEVA Logistics, a world leader in logistics, and its air freight division CMA CGM AIR CARGO, the CMA CGM Group is continually innovating to offer its customers a complete and increasingly efficient range of new shipping, land, air and logistics solutions.
Committed to the energy transition in shipping, and a pioneer in the use of alternative fuels, the CMA CGM Group has set a target to become Net Zero Carbon by 2050.
Through the CMA CGM Foundation, the Group acts in humanitarian crises that require an emergency response by mobilizing the Group’s shipping and logistics expertise to bring humanitarian supplies around the world.
Present in 160 countries through its network of more than 400 offices and 750 warehouses, the Group employs more than 155,000 people worldwide, including 4,000 in Marseilles where its head office is located.
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 coor-dinate a team of Data Architects (external resources initially): you will monitor their work, ensure con-sistency 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)
o Promote Data Architecture strategy & vision
o Lead and coordinate a pool of Data Architects (primarily external partners)
o Plan, prioritize, and allocate architecture work across initiatives and domains to maximize impact and coherence
o Ensure consistency of architectural approaches, models, and deliverables across all Data Architects
o Provide day to day guidance, coaching, and feedback to Data Architects to develop their expertise and align them with Group standards
o Define and monitor expectations and deliverables
o Build and ensure proper animation of the Data Architecture community (rituals, best practice sharing, documentation, training)
o Ensure alignment with Group data strategy and Enterprise architecture principles
2. Data Architecture:
o Update and maintain the target data platform architecture to build the Single Source of Truth and support current and future Analytics & AI needs
o Urbanize the data landscape by structuring domains, data products, and shared capabili-ties
o 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:
o Define modeling standards, patterns, and best practices (conceptual and logical models)
o Lead and review the design of complex data models across domains (analytical, data vault, dimensional/star schemas, semantic models)
o Guarantee the semantic consistency, normalization where needed, and optimal denormalization for performance and usability
o Ensure data models are robust, evolutive, and designed for reusability across multiple use cases and data products
o 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
o Define the data product blueprint (contract, SLAs, quality criteria, ownership, classifica-ion, metadata, documentation)
o Design and continuously improve the delivery process for data products (methodology, templates, gates, design authority and governance)
o Lead and standardize the end to end data product lifecycle process: framing, design, build, test, certification, deployment, and evolution
o Work with business stakeholders and Analytics/AI teams to translate use case requirements into sustainable, reusable data products
o Ensure traceability and lineage from source systems to data products, enabling trust and explainability
o Implement a robust data product certification framework (quality checks, UAT, Run organization, deliverable sign offs, …).
5. Cross Functional Leadership & Collaboration
o Act as the architectural lead and primary point of contact for data platform and data product architecture topics
o Collaborate closely with Business stakeholders, Enterprise & Solution Architects, Data En-gineers, Data Scientists, AI/ML engineers, and Data Governance & Data Management experts
o Influence and align technical and business stakeholders around a common data architecture vision and roadmap
6. Technology Watch & Continuous Improvement
o Evangelize modern data architecture, data product thinking, and platform capabilities across the organization
o 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 architec-ture 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
- Strong experience in data warehousing and analytics modeling (e.g., dimensional/star schemas, 3NF).
- Solid experience with Data Vault 2.0 methodology
- Ability to challenge and optimize existing models for performance, scalability, and main-tainability
- 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 (e.g., Atlan)
- Data quality & observability (e.g., Sifflet)
- Master Data Management (e.g., Semarchy)
- Demonstrated ability to define and run data architectural standards, review boards, or design au-thorities.
Please ensure you are familiar with the CMA CGM Corporate Internal Mobility guidelines
