About Quentin
🚀 Lead Fullstack & Node.js Architect - 7+ years of experience
🎯 WHAT I CAN DO FOR YOU:
- Complete development of your SaaS application (Front + Back + DB).
- Modern and fast stack: Nuxt.js / Node.js / Tailwind / Supabase or Mongo.
- Implementation of best practices from day one (CI/CD, Security, Scalability).
- Node.js & Database performance audit.
- Architecture redesign (Monolith -> Microservices or Serverless transition).
- Mentoring your teams (Node, Best practices).
đź› MY PREFERRED TECHNICAL STACK :
- Frontend : Vue.js 3, Nuxt.js (Expert), React.js, Tailwind CSS.
- Backend : Node.js (Nitro, Express, Nest logic), TypeScript.
- Data : PostgreSQL, MongoDB, Redis.
- Cloud & DevOps : AWS, Docker, CI/CD.
🏆 THEY TRUSTED ME :
- Quadient : Tech Lead on a critical architecture (13M events/day).
- L'Oréal / Bweez : Worldwide deployment of connected Retail solutions.
- Win-Win : Real-time architecture (Socket.io) for virtual events "e-live".
Italian
Conversational
German
Basic
English
Fluent
French
Native or bilingual
Experience
- QUADIENTBack-end Developer & BI Tech LeadTECHMay 2021 - May 2025 (4 years)Avignon, FranceAssignment within a major industrial group for the Packcity solution (world leader in connected lockers).
- Context : International critical environment (EU, US, JP, APAC).
- Volume : 13 Million events/day across ~25k machines.
- Challenge : "No Event Lost" policy (High Availability).
đź§ LEADERSHIP & METHODOLOGY (Soft Skills)
- Agility & Scrum : Working in Squads organized by components. Active participation and facilitation of rituals (Dailies, Retros, Refinements).
- Technical Mentoring : Daily support for developers (Juniors & Seniors) through intensive Pair Programming and demanding Code Reviews.
- Referent Role : Primary technical contact to translate Product Owner needs into concrete BI architecture solutions.
đź› MISSION A: "CORE" PROJECT
Maintenance and evolution of the core system (Locker orchestrator).- Real-Time : Evolution of the bi-directional engine (Machine commands & Sensor feedback).
- Microservices : Development of new services (within an ecosystem of ~30 microservices) and securing via Contract Testing / E2E.
- Migration : Development of a hot-swap system to integrate a competitor's fleet (~2000 machines) without downtime.
- Stack : Node.js, ElasticSearch, RabbitMQ, Redis, K8s.
📊 MISSION B: "BI" PROJECT (Data)
From Scratch creation of a BI architecture for fleet management.- Architecture : Design of a dedicated infrastructure (~10 microservices) ingesting +200M events.
- Unique Expertise : Sole Node.js expert in the team, ensuring the skill development of the other 3 developers on the stack.
- Stack : Node.js, Prisma, PostgreSQL (Aurora), RabbitMQ.
- Closer appsFounder & Fullstack Tech Lead (E-commerce Shopify Marketplace)E-COMMERCESeptember 2025 - December 2025 (3 months)Lyon, FranceDesign and launch of an application for the Shopify ecosystem (E-commerce), aimed at maximizing merchant conversion rates.
🎯 CONTEXT & CHALLENGE:
E-commerce merchants need aggressive strategies to recover abandoned carts or facilitate affiliate marketing. The challenge was to enable the mass generation of "pre-filled cart links" (Permalinks) capable of automatically applying discounts and attributing sales, all without slowing down the store.đź› TECHNICAL ACHIEVEMENTS:
- "Serverless-like" Architecture : Design of a lightweight architecture without a heavy relational database to minimize maintenance costs and maximize profit margins.
- Performance & Pricing Logic : Use of Rust (Shopify Functions) to execute discount logic directly within the Shopify checkout (latency < 5ms).
- ROI Tracking : Development of a precise tracking system to calculate the return on investment for each generated link.
- Stack : Nuxt.js, Shopify Polaris, App Bridge, Unstorage (Key-Value), Rust.
- Capac.proFounder & Fullstack Tech Lead (AdTech)SOCIAL NETWORKSMay 2025 - September 2025 (4 months)Lyon, FranceDevelopment of an automation solution for LinkedIn Ads experts.
🎯 CONTEXT & CHALLENGE:
Managing LinkedIn ad bids is complex and volatile. Campaign managers spend hours manually monitoring their daily budgets to avoid overspending or underspending. The goal was to create a "Co-pilot" capable of adjusting bids in real-time, 24/7.đź› TECHNICAL ACHIEVEMENTS:
- Prediction Algorithm : Creation of a "Confidence Score" that analyzes the budget spending speed and predicts the end-of-day outcome.
- Real-Time Automation : Implementation of asynchronous Workers (BullMQ + Redis) to scan ad accounts and adjust bids via the LinkedIn API without human intervention.
- User Feedback : Responsive interface with Server-Sent Events (SSE) to display the bot's actions live.
- Stack : Nuxt.js, Nitro, MongoDB Atlas, Redis, Scaleway.
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Education
- EngineerEcole des Mines d'Alès2017
- DeveloperEcole 42