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.

Langues

Anglais
Bilingue ou natif
Français
Bilingue ou natif

Préférences en matière de lieu de travail

Accepte de travailler sur site

Paris (jusqu’à 50 km)

Quiet
Data Engineer
EDITION DE LOGICIELS
avril 2023 - novembre 2025 (2 ans et 7 mois)
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
HIGH TECH
août 2021 - février 2023 (1 an et 6 mois)
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
HIGH TECH
août 2020 - août 2021 (1 an)
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