Those who accompany you in your transformation

Romain is a Data Engineering and Cloud expert with over 11 years of experience. For several years he was Lead Developer on high-performance Smart Building products. There he built and shipped engines that take in hundreds of thousands of sensor readings per minute. He also built clustered databases that hold more than 10 million live records. He is certified Microsoft Azure DevOps Engineer Expert. He works across back-end code (Python, C#), DevOps (Docker, Kubernetes, Terraform) and LLM agents. At DataScientist he teaches Python, cloud, DevOps and applied generative AI. He has one goal: help each learner design and ship systems that truly scale in production.

Florian is an Apache Kafka expert and Senior DevOps Engineer. He has over 10 years of experience with real-time streaming platforms. He has built them for major French firms: Crédit Agricole, AXA, Colissimo and Unibail. At Crédit Agricole he co-built and ran one of the largest Kafka platforms in France. It is a Topic-as-a-Service offer. It covers about fifty clusters and more than 100,000 topics. In production it handles close to 1.5 million events per second. He is an ESIEA graduate and a speaker at Confluent events. He also writes code for the open-source Kafka-Python library. He knows the full data-in-motion stack: Kafka, Kafka Connect, Spark Streaming, Ansible, Terraform and Kubernetes. He uses Prometheus and Grafana to watch it all. At DataScientist he teaches the same standards he uses at work: build streaming pipelines that are safe, sound and able to scale.

Valentin is a Data Engineering expert and a software engineer from Polytech Lyon. He has over 10 years of experience across software, real-time data and product. He has built and shipped demanding SaaS platforms. At Hxperience he worked on Smart Building. Then in New York at Vero he led the tech team and later the product, where he drove rental screening tools and helped the firm raise a Series B. Today he is Lead Product & Engineering. He works with Python/Django, REST APIs, microservices and clean software practice: automated tests, CI and code review. He is a key teacher on the Modern Data Engineer Master's. He trains learners to design code you would ship to production without fear.

Dung is a full-stack developer from INSA Centre Val de Loire. He has over 5 years of experience with Next.js, React.js and JavaScript. He designs and maintains the DataScientist.fr learning platform that learners use every day. He builds fast, accessible and polished screens, smooth paths through each course, instant feedback and built-in live coding. His focus is simple: use design to make learning work better. He removes every bit of friction between the learner and the skill they came for. He turns the teaching goals of the expert team into a product that is stable and pleasant to use, from the first click to the final certificate.

Anass is a Data Engineering expert and Talend specialist with over 12 years of experience. He has run critical data projects in production for large industrial and healthcare firms. At Michelin he moved more than 250 Talend routes to Azure and added real-time monitoring. At Almerys he helped rebuild a system that handles over one billion rows per month for 12 million insured members. At Limagrain he led the Talend 7.3 to 8 upgrade, which cut infrastructure costs sharply. He works with Talend ETL/ESB, real-time monitoring (Grafana, Prometheus, ELK), cloud, DevOps and tuned SQL. As a trainer he stays practical and uses real cases with high stakes. His belief: you become a true data engineer by shipping pipelines that hold up.

Cristian is a Machine Learning Engineer from Université de Technologie de Compiègne (UTC). He has over 6 years of experience in Big Data and machine learning in production. On his projects he has built distributed processing pipelines and shipped models at scale, where a notebook is no longer enough. He is an expert in Python, PySpark, Spark and Scala, and works well on cloud and Microsoft Fabric. He knows just what turns a prototype into a solid system that runs on a cluster. As a trainer he is known for staying practical. He has learners work on real cases and huge volumes, not toy examples, so they can ship machine learning that holds up.