Ingénieur(e) En Gestion De Données ML
Core
Design, build, and operate foundational Data Management/MLOps platforms and enterprise hybrid-cloud foundations enabling data and ML workloads across on-premises and public-cloud environments.
Role type
Senior/Expert Data Management and MLOps Platform Engineer
Builds
Governed landing zones, access controls, CI/CD pipelines, IaC modules, and secure data flows
Domain
Enterprise Cloud, Data Engineering, MLOps
Deliverable
infrastructure
Required skills
Python, Go, SQL, Terraform, Kubernetes, Docker, GitOps, Apache Airflow, Apache Spark, Kafka, AWS/Azure/GCP
Preferred skills
Master's degree, 10+ years experience, SageMaker/Vertex AI
Technologies
Terraform, Kubernetes, Helm, Flux, Apache Airflow, Apache Spark, Kafka, AWS, Azure, GCP, SageMaker, Vertex AI
Responsibilities
Architect and enable Data Management/MLOps platforms and enterprise hybrid-cloud foundations; Develop advanced CI/CD workflows with automated gates for model drift and data quality; Build reusable Infrastructure-as-Code modules for landing zones and security controls; Manage secure, auditable data flows implementing governance and lineage capabilities; Serve as a technical leader and mentor for junior engineers; Apply and evolve SRE/DevOps/SecOps practices including end-to-end observability
Seniority
Senior (5-8 years) or Expert (10+ years)
