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Cloud Services at GCP, AWS and Azure: architecture choices, use of storage & compute services
Docker and Kubernetes: containerization & orchestration of applications, management of K8s
Python programming: development of server-side tools (bulk data processing, REST API server
CI/CD: managing the integration and ongoing deployment of our applications and internal platforms
Data pipelines: development of ETL scripts in Big Data environments
Infrastructures & Services adapted to Machine Learning: technology watch and implementation of

Master's Degree with a strong quantitative component (e.g. Econometrics, Physics, Mathematics
1-3 years of relevant experience in Data, DevOps, Cloud or Software Engineering
Good level in Python and solid foundation in other languages
Familiar with at least one SQL DBMS (ideally PostgreSQL) and ideally noSQL (ideally MongoDB)
Ideally familiar with at least one cloud services platform (GCP, AWS, Azure)
Comfortable with Docker, automating CI/CD pipelines, and strong appetite for Kubernetes

Consultant Data Engineer

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