Data Platform Engineer (DevOps)

Capgemini is an AI-powered global business and technology transformation partner with over 420,000 team members in more than 50 countries. The Insights & Data team delivers state-of-the-art Data solutions focused on Cloud & Big Data engineering, utilizing platforms like AWS, Azure, and GCP, and supporting AI projects in Generative AI, NLP, Anomaly Detection, and Computer Vision.

• At least 3 years of experience in a similar role, including 1+ year working with cloud platforms.
• Strong experience in Python or another programming language.
• Hands-on experience with DevOps methodologies, especially Infrastructure as Code (Terraform, Bicep).
• Very good communication skills and strong English language skills.

Nice to have:

• Experience with CI/CD pipelines and automation tools.
• Familiarity with cloud data services such as Data Lake, Snowflake, or Synapse.
• Knowledge of containerization (Docker, Kubernetes) and cloud security best practices.
• Certifications such as AWS Certified Data Analytics, Azure Data Engineer Associate, or GCP Professional Data Engineer.

• Automate the deployment and management of cloud-based data platforms using Infrastructure as Code (IaC).
• Develop and maintain CI/CD pipelines to streamline data engineering workflows and deployments.
• Optimize system reliability, scalability, and security by implementing DevOps best practices.
• Monitor, troubleshoot, and enhance cloud-based data infrastructure to ensure high availability and performance.