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Cloud Services at GCP, AWS and Azure: architecture choices, use of storage & compute services
Docker and Kubernetes: containerisation & 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 familiar with at least one cloud services platform (GCP, AWS, Azure) with experience mixing
Comfortable using Docker, automating CI/CD pipelines, and strong appetite to gain competence in
Able to work in a DevOps culture, responsible for code lifecycle; mastery of Gitlab-CE ecosystem is

Data Engineer Consultant

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