Yohan Yakoub

I worked within the Global Cloud Competence Center for Sodexo, where the objectives were:

- Ensure a standardized and reference base for cloud transformation on Azure and provide the rules to follow.

- Provide a documented and accessible set of practices, processes, tools, techniques, and templates.

The first objective is to define within the CCOE (Cloud Center of Excellence) documents such as Service Enablement and Hardening Guide. Define technical design use cases tailored to clients and integrate cybersecurity standards.

A second objective is to provide a global Kubernetes Machine Learning platform for the CRAFT program. Implementation of a global Saint Gobain Container solution based on Kubernetes (ContainerForSG), with integration of SecOps and FinOps aspects. Participation in workshops for Landing Zone version 2, initially intended for opening up to North and South American countries, and secondly for improving the design of Landing Zone version 1.

Assisting projects (around 15 projects) in their migration to the Cloud, as well as Landing Zone V2, defining architecture designs, and implementing Cloud recommendations. Azure governance is a crucial aspect of a company's cloud infrastructure, as it ensures the security, compliance, and efficiency of its cloud operations. As an experienced Azure professional, I have a solid background in Azure governance, including the implementation and configuration of compliance policies, identity and access management, monitoring, and cost management. I have also worked on data migration projects to Azure, ensuring strict governance to guarantee that sensitive data is stored and managed securely and in compliance with company standards. With my in-depth knowledge of Azure governance, I can ensure that the company's cloud operations are secure, compliant, and optimized, which can be a valuable asset to any company seeking qualified Azure professionals.

DSI - Data Department

• Project 1 Title: PowerChef (7 people)

• Project 2 Title: Data Platform (15 people)

• Project 3 Title: Food Recognition (5 people)

• Project 3 Title: Spend IQ (5 people)

The general objective of the projects on which I have contributed (Data Platform, IFM, PowerChef, etc.) is to evolve machine learning models in three use cases of Data Insights developed by the client in order to maximize the machine learning potential taking into account business rules. The first stage of the project focuses on 1 use case. Business. Enterprise: The use case is to provide a solution for site managers to increase the number of application resources, following three models of machine learning. Provide a BIG DATA data platform on AZURE for ingestion processes.

Technical : Azure - DevOps - FinOps - SecOps - DataFactory - DataBricks - Azure Machine Learning - Docker - Kubernetes - ARM - Python - .NET - Scala - R