Description

Certifié GCP Professional Data Engineer et Apache Airflow 3 DAG Authoring (Astronomer), j'accompagne les entreprises dans la conception d'architectures data robustes, automatisées et performantes.

Fort de plus de 5 ans d'expérience, mon approche combine une expertise Cloud pointue avec une rigueur logicielle issue de mon background en Backend Engineering - Python/Java.

Mon objectif : transformer vos flux bruts en actifs stratégiques tout en optimisant vos coûts.

🚀 Ce que je peux vous apporter :

Architecture & Infrastructure (IaC): Conception de plateformes data de A à Z, industrialisées via Terraform ou Pulumi.

Pipelines de données (ETL/ELT): Mise en place de flux scalables avec Airbyte, Cloud Run et orchestration avancée via Airflow.

Modélisation & Performance: Transformation de données avec dbt / Dataform sur BigQuery, optimisée pour des volumes allant jusqu'à des centaines de milliards de lignes.

Observabilité & DataOps: Mise en place de monitoring et d'alerting en temps réel (réduction du temps de détection d'incidents de 80%).

🛠️ Mes types de projets habituels :

Mise en place de Data Stack moderne: Déploiement complet de l'écosystème BigQuery / dbt / Airflow.

Migrations Cloud complexes: Transition de systèmes legacy ou on-premise vers des architectures Cloud Native.

Industrialisation de l'IA: Déploiement de modèles de Machine Learning, connexions LLMs, orchestrations d'agents.

Développement d'outillage Data: Création de SDK et middlewares sur-mesure pour faciliter l'accès et la qualité des données.

Languages

English
Native or bilingual
French
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

Quiet
Data Engineer
SOFTWARE PUBLISHING
April 2023 - November 2025 (2 years and 7 months)
Paris, France
As the sole Data Engineer, established the GCP data architecture from scratch to support batch analytics pipelines for 35+ games/apps with millions of users generating data.
- Designed and built ELT pipelines using Airbyte, cloud run functions and event driven scheduling data ingestion from diverse sources; Managed transformations using Dataform (DBT) running on BigQuery;
- Migration of Airbyte from Google Kubernetes Engine (GKE) to Google Compute Engine (GCE) machines, resulting in substantial cost reduction (45%)
- Established observability frameworks (metrics and real-time alerting) for key KPIs monitoring apps in production, reducing critical SDK issue identification time by up to 80% (5-6 days to 1-2 days).
- Implemented task automation, resulting in a 4-5 hour reduction per team per week in report writing and filing responsibilities; Slack bots to deliver daily key metric notifications tailored to specific division
- Data Volume: 10s of Millions of rows daily
Skills: BigQuery, Dataform, DBT, Airbyte, GCE, CloudSQL, Pulumi, cloud functions, GCP, Python, GitHub Actions
Google Cloud Storage Big Query SQL Python DBT
Symphony - Licorne
Data Engineer
TECH
August 2021 - February 2023 (1 year and 6 months)
Nice, France
Hired early and contributed to scaling from 24 to 150+ in France office, fostering a high-stakes, highly technical scale-up environment
- Created and maintained high-performance BigQuery SQL queries at scale to reliably power all critical customer-facing dashboards (JP Morgan, Deutsche Bank ...), ensuring data accuracy and freshness for critical product features. All SQL queries were Terraform templates to be promoted and tested on 4 environments before PROD.
- Reduce by 80% customer review triaging time by deploying NLP models for sentiment analysis and topic clustering
- Maintained and monitored Google Dataflow reading from multiple sources writing to GCS
- Data Volume: 100s of Billions of rows, BigQuery tables and SQL queries needed to be optimized for load and processing. Hundreds of BI datasets and 100s of BI ETLs.
skills: BigQuery, GCS, Cloud Run, Dataflow, Dataform, Vertex AI, Python, Terraform, Domo
Big Query Dataform SQL Python Vertex AI
Symphony - Licorne
Backend Engineer
TECH
August 2020 - August 2021 (1 year)
Nice, France
- Developed, maintained, and published open-source Python (from scratch) and Java SDKs, ensuring high-quality, reusable compo nents for external developers on the Symphony platform.
- Design and develop of a middleware using Kafka, Spring and MongoDB to serve external platform organizations.
- Contributed to the development and maintenance of both legacy monolith and new microservices, operating in a highly rigorous engineering environment that enforced minimum 95% testing coverage verification on every Pull Request.
- Assumed a rotating "full-time fireman" role for client support, demonstrating deep ownership and rapid problem-solving skills to ensure high availability and stability of core platform services.
skills: Python, Java 8/11, Quarkus, Spring boot, Kafka (Distributed Systems), mongoDB (NoSQL), AWS
Python MongoDB CI/CD SQL Apache Kafka