Sofiane Kihal

• GCP Foundations Architecture • GCP Foundations design and deployment (IAM, Network, Security, CI/CD, Monitoring) • CI/CD design and implementation (GitHub, Gitlab, Cloud Build, Docker, Terraform) • IAC design and implementation (Gitlab, Terraform) • Monitoring dashboards design • Data Governance strategy design and implementation • GCP Data Architecture (Medallion Architecture implemented) • Requirement gathering from business team, design and implementation of Data Products • Dataform ELT and deployment design (CLI with CI/CD) • Cloud Composer architecture design and deployment • Dataproc Hub - JupyterLab design and deployment for Data Scientists • Datastream with private connectivity design and deployment • Data loading solution with Cloud Run Functions (Python), Pub/Sub, Cloud Storage • Python development framework design and implementation • PySpark code design and optimization • SQL development for business needs • Multi-Cloud network connection to Shared VPC network design and deployment • Private Google Access set up on each network peering design and deployment • VPC Service Control implementation • Confluence documentation structure design • Technical documentation (DAT) • Customer Encryption key management • Workload Identity Federation • Technical documentation (DAT)

Within the Marketing & After-Sales Performance Europe Department, linked to the team responsible for developing Data Intelligence in the management of Renault workshops' business in Europe. • Development, testing, and deployment of algorithms for predicting vehicle workshop visits. • Application of Machine Learning algorithms (Random Forests, GBT, Multiple Linear Regressions, etc.) to model workshop visits based on vehicle history and technical information. • Use of tools such as Hive, Spark, Jupyter, Zeppelin to process billions of lines of available data. • Communication with Marketing managers from each European subsidiary (20 different countries) to understand their needs and explain the results.

• Specification, design and development of modules for the systematic extraction of massive data (macro and financial data, satellite images, open data ...) • Implementation and deployment of Big Data data storage structures • Design and development of the internal API for querying massive data • Implementation of tests and monitoring indicators • Writing technical documentation

Finalist winner of the Entreprendre Projects Challenge (2nd place) The Entreprendre® Projects Challenge is the largest entrepreneurial projects competition in France. It was created in 2000 by Télécom SudParis and Télécom Ecole de Management.

Member of the Insta Farmer team as part of an entrepreneurship project with IMT Starter. Development of tools to improve audience efficiency on Instagram.