Expert, Senior
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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.
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
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
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
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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