In order to strengthen the technological pole of QuantCube Technology , the company is in particular looking for a profile with experience in development and data processing.

The missions on which you will be particularly likely to intervene include:

• Development, Implementation and Maintenance of large-scale Big Data systems
• Building data pipelines on Cloud infrastructures
• Deployment on Cloud infrastructures
• Interpretation, Adaptation and Implementation of complex Machine Learning algorithms towards a distributed architecture
• Implementation of data transfer structures to NoSQL databases
• Implementation of infrastructure and service monitoring tools
• Technical watch and Documentation on the latest innovations in the field of analytical solutions and processing of massive data

You will have the opportunity during these missions to discover, distributed file systems and NoSQL databases. You will also be able to acquire real experience of the development cycle within an innovative start-up, from the collection of needs to the production of deliverables, including technical analysis, design, modelling, production and testing.

You are passionate about new technologies, and attracted by the prospect of evolving in a startup environment around Artificial Intelligence. You are passionate about Big Data projects and you have a particular interest in the role of data architect and in the study and design of advanced computer systems. You have a good level of English, show initiative and autonomy and enjoy challenges.

You also have strong skills in the following subjects:

• Python
• Big Data Technologies (NoSQL databases, Spark)
• SQL and relational database technologies
• UNIX commands and Linux development
• Good development practices: versioning, testing, role management

Knowledge and/or experience in the following subjects is a plus:

• Security / Network Administration
• Cloud computing
• REST API

QuantCube recruits and recognises all talents

1. Meet the Recruiter and Directeur Infra (30 min)
2. Technical interview with 2 Data Engineer (1h30)
3. Meet the co-founders (30 min)