Description

I am fond of python and Rust ontop of kubernetes.

Tasks that I like:

- Building python data collector framework making ingestion fast and easy (leveraging DB or filesystem).

- Making lightweight realtime aggregation and data processing with Rust.

- Using FastAPI, Actix-web, PostgreSQL backend and language agnostic message queueing like rabbitMQ or ZMQ.

- Packaging the code as CRI runtime.

- Building kubernetes cluster with ansible and deploying pods on it.

- Building nice dashboard with kube-prometheus-stack and grafana.

- Using Loki as cheap but lightweight solution for observability.

Above tech suite are things I have been used to do, I am yet eager to adapt and learn new tools.

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km)

LFIS Capital.
Quant Dev
October 2025 - Today (8 months)
I built a new data platform within a MF equity trading desk. Deliveries include:
+ Ansible playbooks to setup a k8s on prem on debian VMs. Leveraging charts such as longhorn,
kube-prometheus-stack, Loki with alloy, Minio as a s3 storage service, argocd and argo-workflows.
+ Python library development to ease ETL deployment to extract data from S&P CIQ, computeStat
datasets.
BNP Paribas.
Senior Python and k8s developer
January 2025 - July 2025 (6 months)
Within a junior team within anti-money laundering IT, I aimed at raising python and modern tools as
standard and build a new data platform on k8s. This platform needs to help research design new rules for money laundering detection, as well as execution of such rules. Deliveries include:
+ Code refactoring of current solution into python. Improving software, packaging and deployment.
+ Oracle DB integration, FastAPI based REST API, SQLAlchemy for SQL migration, SQLModel as
ORM.
+ Argo-workflows for rule execution on kubernetes.
QRT
Quantitative Technologist, python backend engineer
June 2021 - June 2024 (3 years)
Paris, France
1. Developpement de nouvelles techniques pour la mise en cache sur un SI de plus de 1000 sources de
donnees. Etude statistiques sur les requetes et modification sur le serveur backend pour reduire les
evictions de cache degradant la recuperation de donnees. Developpement de scripts utilitaires autour
du cache.
2. Contribution au client python au service de souscriptions websocket serveur permettant l'ecoute de
topic Kafka.
3. Support sur les questions de recuperations de donnees (problemes client-serveur).
4. Developpement d'une librairie python a destination des equipes de recherche pour permettre
le developpement de micro-services de traitement de donnees. Monitoring sur prometheus DB,
deploiement sur kubernetes. Gestion de ce parc de pods kubernetes (equipe fixed-income, pods
realisant de la generification et calcul de courbe de taux en temps reel sur les swaps et les bonds).
5. Developpement d'une fonctionnalite de test record/replay, facilitant le developpement de tests
d'integrations sur des process statefuls.
6. Developpement et support de scripts d'extractions de donnees sur des fournisseurs de donnees
permettant la recherche d'alpha. Packaging en image docker et deploiement sur kubernetes ou
Amazon ECS en micro-service. Ex: Blooomberg, Markit data stream, IIR (donnees de raffineries de
petrole), Ravenpack (sentiments). Protoles divers utilises tel que FTP, REST APIs, des connexions
SQL ou websockets.