Your objective will be to facilitate and accelerate the development of all projects within the Data Science, Data Analysis and Data Visualization divisions of the Analytics Factory, by introducing cross-functional processes, tools and DevOps expertise throughout the development cycle, from the first prototype to production deployment and ongoing maintenance.

You will be amen:

• Establish, maintain and improve the continuous integration and deployment (CI/CD) processes of cloud infrastructures for analytical projects (including AI and agentics).
• Administer and maintain the shared services of the Analytics Factory (Airflow, Langfuse, semantic layers, etc.).
• Demonstrated respect for good practices and safety rules.
• Identify opportunities to improve and automate service offerings, while remaining attentive to the needs of analytical teams.
• Providing daily support to the engineering community: deployment, application configuration, access management, incident investigation, cloud cost optimization.
• Deploy and manage Kubernetes clusters and associated applications.
• Use GCP (GKE, Cloud Storage, Cloud SQL, Cloud Monitoring).
• Administering Apache Kafka from advanced configuration to production operation (performance, security, monitoring).
• Implement good security and access management practices.
• Scripting in Bash, Python or equivalent for automation.
• Analyze the technical impacts and improve existing solutions.

Desired Candidate Profile

Candidates must hold a Master's degree (Bac+5) from an engineering school or equivalent university degree with a specialization in computer science, or have equivalent significant experience.

Experience : More than 7 years of experience in DevOps and/or Data Engineering.

Experience in the retail/mass distribution sector is an advantage.

Required skills:

• Must-haves: software development, CI/CD, cloud deployment (preferably GCP), infrastructure as code, containerization and Kubernetes orchestration, and a thorough understanding of network issues

• Nice to have: GCP (GKE, Cloud Storage, Cloud SQL, Cloud Monitoring), Apache Kafka (advanced configuration, production), Bash/Python, relational databases, DevOps and Agile practices, access management, and cloud security