Remuneration
Profit-sharing and employee savings plan, works council, concierge service, group sports classes, meal vouchers, time savings account, and three days of volunteering with the corporate foundation
Location
Cluses, ARA, France
Visa sponsorship
Not specified
Job summary
The Platform Engineer builds, operates, and evolves shared capabilities for a Data Platform, enabling Data, Analytics, and AI teams to deliver products autonomously in a reliable, secure, observable, performant, and cost-conscious environment. The role turns engineering standards into self-service services, reusable components, Infrastructure as Code modules, CI/CD pipelines, templates, and golden paths, while improving platform architecture, resilience, security, and developer experience. The technology landscape includes Azure, Terraform, Docker, Kubernetes, Snowflake, Airflow, and observability tools such as Grafana and Prometheus.
Benefits
Profit-sharing and employee savings planWorks council benefitsConcierge serviceGroup sports classesMeal vouchersTime savings accountThree days of volunteering with the corporate foundation
Qualifications
- Experience in Platform Engineering, Data Engineering, Cloud Engineering, or DevOps.
- Experience designing and operating platforms or shared technical services.
- Experience with automation, CI/CD, and Infrastructure as Code.
- Experience operating production environments and resolving reliability, performance, or security issues.
- Strong knowledge of several relevant areas, such as public cloud, containers, orchestration, modern data platforms, observability, security, or scripting.
- Ability to understand and evolve platform engineering patterns and collaborate with multiple stakeholders.
Responsibilities
- Design, build, and maintain shared Data Platform capabilities for compute, storage, orchestration, CI/CD, observability, security, and data services.
- Automate platform provisioning, configuration, deployment, and operations using Infrastructure as Code, pipelines, templates, and reusable components.
- Maintain platform availability, resilience, performance, scalability, and cost efficiency.
- Implement identity and access controls, including IAM, RBAC, secrets management, and environment separation.
- Provide self-service environments and standardized development, testing, deployment, and operations paths for Data, Analytics, and AI teams.
- Monitor platform services, resolve incidents, manage upgrades and decommissioning, and address technical risks and debt.
- Maintain technical documentation, examples, templates, and user guides; support teams adopting platform capabilities.
Skills
AirflowArgo CDAzureBashdbtDockerGitLabGitLab CIGrafanaIAMKubernetesPrometheusPythonSnowflakeTerraform
Work schedule
Hybrid work: two remote days per week on average, up to 90 days per year after o
Industry
Data platformsData engineering
Relocation
No