Passionate about Data, AI and Software Engineering.
I’m currently working as a Staff Data Engineer at Back Market. I love to lead data projects to help the business make the right data-driven decisions. As a doer and an open-source enthusiast, sharing my knowledge with others and helping them grow makes my day better.
September 2012 - September 2013
Dauphine-PSL and MINES Paris-PSL, Paris, France
September 2009 - May 2012
INP-ENSEEIHT, Toulouse, France
Software Craftsman with a strong knowledge of several programming languages.
Focus on building structured, high-quality data solutions on different cloud providers. Besides, I had several experiences in building and maintaining highly scalable ETL pipelines and data-powered applications.
Having been in different leadership positions, my energy is focused on coaching and upskilling engineering teams members while sharing a broad vision on designing complex architectural evolutions that impact the business.
Experience working with AWS and GCP cloud services for designing multi-region architecture that meets scalability, availability, performance, and security considerations.
Explore the evolution of Back Market’s GenAI platform, Monster AI, from prototype to robust product, offering modular, flexible, and vendor-independent solutions that integrate with various AI technologies, while focusing on data security, privacy, and the human and technical challenges, sharing successes, failures, and lessons learned in meeting business expectations and user needs.
From prototype to product, Back Market has developed its own internal GenAI platform, Monster, aimed at being modular and secure.
The experience begins with the need to provide ChatBot-type experiences using AI. Born as a side project, the platform hosted on GCP and based on chainlit, evolves through experiments and business scenarios that arise. Monster is designed from the start to be modular, flexible, and independent of the providers used. It can connect to Vertex AI, OpenAI, or others, allowing the business to adapt Monster AI to needs effortlessly. However, Monster AI does not neglect the security and confidentiality of data, which are essential pillars of our implementation choices. We will show the challenges encountered and security features developed to ensure the scalability and reliability of AI projects for our 700 internal employees or by enhancing the productivity of more than 150 of our support agents. Despite the technical appearances, this has also been a human challenge, on which we will share our successes but also our failures, from responding to strong business expectations to neglecting a segment of users. Our session explores the challenges, breakthroughs, and implementation choices, from prototype to product, with the necessary hindsight to share our lessons and advice. Join us for an in-depth exploration of the challenges faced, significant advancements made, and valuable lessons learned.
In this episode, Florian Valeye, Staff Data Engineer at Back Market, talks about Delta Lake, a Linux Foundation project to provide reliability, performance and quality on data lakes. He also talks about Rust programming language and why it’s one of the most loved languages among developers.
This conversation from the Open Source Summit in Spain provides valuable insights into the significance of Delta Lake, the role of Rust in data engineering, and the collaborative nature of open source communities.
Creator of the delta-buddy, an AI ChatBot to ask anything about your Delta Lake.
Creator of the tracarbon, a Python library to track your carbon emission.
Creator of the metadata-guardian, a Python library using Rust to scan metadata sources.
