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Objectifs et livrables Key Responsibilities Platform Build and Delivery (Core Responsibility) Responsibilities Design and implement the Self-Service Data platform architecture Define platform capabilities (data products, pipelines, governance, observability, self-service access) Define and enforce technical standards and architecture patterns Ensure scalability, performance, and security Make hands-on technical decisions and solution validation Expected Deliverables Architecture decision records (ADR) Reference architecture patterns and reusable templates Platform capability roadmap Platform technical standards Cloud Architecture and Infrastructure Responsibilities Drive the Design and operate cloud and hybrid architecture with the Group Data Architect Coordindate with the Group Data Delivery Team the implementation on Amazon Web Services and Microsoft Azure Lead the Integration of on-premise systems Lead the Implemention of automation and infrastructure as code Ensure security and compliance requirements Expected Deliverables Cloud architecture blueprint (with the help of the Group Data Architect) Security and access management framework Delivery and Execution Management Responsibilities Own platform delivery lifecycle Define backlog and prioritization process Manage releases and production deployment Track performance and reliability Manage risks and technical issues Expected Deliverables Platform roadmap (short / mid / long term) Product backlog and prioritization framework Release plan and version management process Delivery tracking dashboards Platform SLA / reliability metrics Deployment and Domain Adoption Responsibilities Deploy platform across business domains Enable domain teams to build data products Deploy Data Mesh operating model Support onboarding and adoption Resolve operational adoption challenges Expected Deliverables Domain onboarding framework and process Data product lifecycle guidelines Domain enablement playbooks Adoption and usage metrics Training materials and onboarding documentation Product Management (Usage-Driven) & Continuous improvement Responsibilities Capture user needs and platform requirements Define product vision and roadmap Measure usage and value delivery Improve developer and user experience Expected Deliverables Product vision and value proposition Platform KPIs and adoption metrics User feedback loops and improvement backlog Platform enhancement roadmap Documentation, Standardization & Governance Responsibilities Document platform capabilities and processes Ensure compliance with group Federated Computational Data Governance Expected Deliverables Platform documentation repository Technical standards and implementation guidelines Governance and compliance framework Best practice playbooks Operational Communication and Executive Reporting Responsibilities Communicate platform progress and impact Provide executive-level reporting Manage stakeholder alignment Expected Deliverables Executive Project Dashboard Platform performance dashboards Steering committee presentations Decisions, Risks and issues tracking Internal Promotion and Evangelization Responsibilities Promote platform value across the organization Support internal adoption initiatives Build platform community Expected Deliverables Internal platform communication materials Adoption strategy and rollout plan Platform demos and use case portfolio Required Experience Minimum 15 years of experience in data platform, data engineering, or architecture Proven experience building and delivering production-grade data platforms Strong experience in hands-on technical delivery and implementation Experience in platform engineering or advanced data engineering Experience in large-scale enterprise or multi-entity environments Practical experience with Data Mesh mandatory. Technical Skills Architecture & Engineering Distributed data architecture Distributed systems design Infrastructure as code DevOps / DataOps / CI/CD practices Performance and scalability engineering Cloud & Infrastructure Advanced expertise in AWS and Azure Hybrid and on-premise architectures Cloud security and governance Data Platform Data products and data lifecycle management Data pipelines and orchestration Metadata and catalog management Data governance frameworks Data observability Product & Delivery Product mindset applied to technical platforms Roadmap and backlog management Agile delivery methodologies Value-driven development Critical Soft Skills Strong technical and operational leadership Execution and delivery mindset Ability to operate hands-on in complex environments Excellent cross-functional communication Strong ownership and accountability Problem-solving and pragmatic decision-making Ability to influence without direct authority Strategic thinking with operational focus Stakeholder management at executive and operational levels Fluent English (mandatory — written and spoken) Success Metrics Platform successfully delivered and operational in production Adoption across business domain Number and quality of deployed data products Platform reliability and performance User satisfaction and platform usage Reduced time-to-market for data use cases

Votre Mission : En tant que PO Data, vous piloterez des projets de transformation sur des produits Data et IA dans des contextes Marketing, CRM, KYC. Vous jouerez un rôle clé dans le cadrage, la structuration et le pilotage de travaux stratégiques, en coordination avec de multiples acteurs internes et externes. Concrètement vous allez : Intégrer un dispositif existant et piloter les nouveaux projets DATA/IA sur l’ensemble des phases : cadrage, Expression des Objectifs, MVP et démarrage des développements. Recueillir, challenger, analyser et prioriser les besoins data des métiers Concevoir les expressions de besoins afférentes Définir la vision data de son périmètre et en construire la roadmap Prioriser les évolutions data en fonction de la valeur pour les métiers et/ou les clients Collaborer avec l’équipe de PO data de tous les périmètres des paiements pour s’assurer de la cohérence de la démarche mise en place Participer aux rituels agiles Garantir la cohérence des données entre les différents métiers, et plus globalement la qualité et la pertinence des livrables data mis à disposition des métiers et/ou des clients Suivre les indicateurs de performance sur son périmètre et mesurer la valeur des solutions mises à disposition Accompagner les utilisateurs dans l’appropriation et l’utilisation des solutions mises à disposition Accompagner les utilisateurs dans l’interprétation et la valorisation des données mises à disposition Garantir la cohérence des jalons et la tenue des échéances de la feuille de route Data et IA. Assurer un rôle de référent(e) sur les bonnes pratiques Data/IA : modèles IA, entraînement et FinOps. Votre futur environnement technique & fonctionnel : · IA / Data : Data engineering, IA Générative, Machine Learning,