Amir Lehmam

Architected and developed a SaaS B2B platform of 16 microservices handling 20,000+ transactions/day; implemented event-driven architecture, asynchronous workers, and AI agents to automate prospecting workflows.

Performed 15+ Data & IA diagnostics including audits, target architectures, roadmaps and financing; deployed GenAI production solutions (RAG, knowledge graphs, agents) and trained 50+ staff achieving >80% adoption.

Developed serverless ETL pipelines into Azure Data Lake Gen2 with end-to-end latency under 5 minutes; optimized queries and partitioning to cut cloud costs by 25% and implemented multi-environment CI/CD reducing deployment time to under 10 minutes.

Developed an automated trading agent supporting 60+ strategies and built tick-data ingestion pipelines; deployed production Azure infrastructure (VMs, PostgreSQL) with automated monitoring and created real-time multi-strategy dashboards for data-driven operations.

• Pilotage d’une migration de reporting (PDF -> Power BI) pour 10+ pays EMEA.
• Automatisation des flux GCP (BigQuery) -> Power BI via Azure Logic Apps et APIs.
• Réduction de 60% du temps de reporting vs workflows Excel manuels.
• Construction de dashboards sécurisés (RLS multi-pays) et formation, adoption > 85%.
• Management agile d’une équipe de 4 développeurs.

Grade: Mention Bien

Completed a Master's program in Innovation, Marketing, Communication & Data Science with mention Bien in 2023.

Grade: Mention Bien

Completed Master 1 in Data Analytics with Mention Bien during the 2021–2022 academic year.

Completed a Bachelor (Honors) in Finance at INSEEC during 2020–2021.

Completed a Licence in Economic and Social Sciences at Université de Paris from 2017 to 2020.