Data & ai platform engineering lead (h/f)

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Osez rejoindre Edenred et préparez-vous à vous épanouir dans une entreprise internationale qui vous offrira des opportunités infinies.

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Venez comme vous êtes, dans le respect de votre singularité et contribuer à l'aventure Edenred avec nous.

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YOUR ROLE

In close collaboration with asset teams, integration engineers, SRE, and product squads, the Data & AI Platform Engineering Lead acts as the technical owner of Edenred’s Data & AI platform foundations.

As a player-coach, the role both designs and builds core platform capabilities (Databricks, Unity Catalog, infrastructure, CI/CD, agent runtime primitives) and coaches teams to use the platform correctly. The role ensures the platform is secure, scalable, observable, interoperable, and AI-ready, while enabling autonomy and reuse across geographies and business lines.

Responsibilities

• Own the Data & AI platform roadmap as a product (Databricks, Unity Catalog, infrastructure, shared services)

• Design and implement core platform building blocks (workspaces, catalogs, compute policies, environments)

• Enforce security, access control, and isolation by design

• Ensure the platform supports data, AI, and agentic workloads consistently

• Contribute hands-on to critical platform components and upgrades

• Define and operate the platform-level agent interoperability layer

• Ensure agents can interoperate across runtimes (Databricks agents, Salesforce Agentforce, internal services)

• Treat agent interfaces as first-class platform APIs, versioned and governed

• Partner with SRE to embed observability, reliability, FinOps into platform primitives

• Co-own CI/CD frameworks and guardrails (policy-as-code, quality gates)

• Participate as a standing member of the Design Authority

• Enable discovery, sandboxing, and fast-track experimentation safely

• Prevent platform fragmentation and shadow architectures

YOUR PROFILE

Technical & Engineering

• Strong background in platform and software engineering

• Deep expertise with Databricks & Lakehouse architectures (Unity Catalog, security, serverless)

• Solid understanding of data engineering and AI enablement needs

• Working knowledge of agent runtimes, tool/function protocols, and A2A interaction patterns

• Comfortable with cloud infrastructure, IAM, networking, and infrastructure-as-code

Player-Coach Mindset

• Hands-on engineer able to design, build, and debug core systems

• Coaches teams through patterns, reviews, and enablement rather than control

• Raises engineering standards through example

Collaboration & Influence

• Able to influence architecture and usage without hierarchical authority

• Clear communicator with engineers, architects, and leaders

• Pragmatic, anti-dogmatic; standards exist to enable teams

• Comfortable arbitrating trade-offs between simplicity, flexibility, and scale

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