DevOps Engineer
Strengthen the cloud backbone behind earth observation, image processing, and environmental data platforms. This senior DevOps role blends platform reliability, security, and big data operations to turn planetary data into actionable insight.
CONTEXT
Our client, a major player in its sector, operates at the intersection of science, technology, and large-scale data services. Its platforms ingest, process, and distribute enormous volumes of earth observation data, transforming satellite imagery and environmental signals into information that researchers, public authorities, and businesses can act upon. Behind these ambitious services lies a cloud infrastructure that must be resilient, secure, automated, and capable of handling unpredictable data flows. The organization is looking for a senior DevOps engineer to reinforce this foundation and help bridge the gap between scientific innovation and operational excellence. Every improvement in deployment speed, platform stability, or security posture directly increases the impact of environmental monitoring and big data analytics.
ACTIVITIES
- Manage, monitor, and improve cloud infrastructure and operational systems supporting earth observation services.
- Resolve DevOps issues across deployment pipelines, runtime environments, networking, and storage.
- Deploy and configure components in public cloud environments using automation and infrastructure-as-code practices.
- Implement security best practices, access controls, monitoring, and incident response procedures.
- Support data distribution, image processing, and Big Data analytics workloads.
- Collaborate with IT architects, software engineers, data scientists, and scientific teams.
- Maintain CI/CD pipelines and improve release reliability, observability, and scalability.
- Document operational procedures and contribute to platform standards and continuous improvement.
EXPECTED ACHIEVEMENTS
- A more resilient, secure, and automated cloud platform for environmental data services.
- Faster and safer deployments, with fewer manual interventions and reduced operational risk.
- Improved monitoring and incident response across critical earth observation and processing systems.
- Scalable infrastructure capable of supporting growing data volumes and analytical demands.
- Strong collaboration between engineering, science, and IT architecture teams.
ENVIRONMENT
- Public cloud platforms and cloud-native services.
- CI/CD pipelines, infrastructure as code, and automation tooling.
- Kubernetes, containerization, monitoring, and observability tools.
- Security best practices, identity management, and network controls.
- Big Data, image processing, and earth observation data workflows.