Description

🚀 Data & IA Engineer | De l’idée à la livraison et adoption de vos produits Data & IA

💡 Vous avez un projet Data ou IA à concrétiser ? Je vous accompagne de A à Z, depuis le recueil de vos besoins jusqu’à la mise en production et l’adoption par vos équipes.

📌 Mes expertises incluent :

• Data Architecture : Conception d’architectures robustes et évolutives.

• Data Pipelines : Implémentation de flux de données Batch & Streaming.

• Orchestration : Optimisation et automatisation des workflows.

• Data Management : Gouvernance des données et qualité de la donnée.

• Data Modeling : Modélisation efficace pour exploiter vos données.

• DataOps & MLOps : Déploiement agile et industrialisation des projets IA.

• Dashboards : Création de tableaux de bord clairs et percutants pour des prises de décision éclairées.

🎯 Pourquoi travailler avec moi ?

• Approche sur mesure adaptée à vos enjeux métiers.

• Expertise technique et méthodologique éprouvée.

• Communication fluide pour un suivi optimal du projet.

👉 Ensemble, transformons vos données en valeur ajoutée !

Domaines d’expertise

Langues

Français
Bilingue ou natif
Anglais
Capacité professionnelle complète

Préférences en matière de lieu de travail

Accepte de travailler sur site

Paris (jusqu’à 50 km)

BNP Paribas
Lead Data Engineer
BANQUE & ASSURANCES
septembre 2022 - Aujourd'hui (3 ans et 9 mois)
Paris, France
As the first Data Engineer in the IT Marketplace department, an ambitious project aiming to centralize all IT offerings within the bank, I was responsible for creating a data platform from scratch, providing the tools, architecture, and culture required to become “Data-Driven.”
Definition of the data strategy and roadmap: Developed and implemented a comprehensive data strategy to align with business objectives.
Self-hosted Modern Data Stack: Deployed and managed self-hosted analytics and data transformation tools (Metabase, DBT) to ensure seamless data operations.
In house ETL/ELT Data Pipelines and DataOps: Designed, developed, and deployed scalable data pipelines, a robust data warehouse establishing a documented, governed and monitored single source of truth.
Tableau/ Metabase Dashboards: Simplified data discovery and access through industrialized and flexible dashboards, providing reliable and up-to-date metrics on a daily basis.
Team training (product, marketing, quality): Conducted training workshops on the use of Tableau dashboards, enhancing the adoption of proposed solutions and maximizing the impact

Tech Stack: Golang, Python, Bash, Airflow, dbt, PostgreSQL, Redis, Kafka, ReactJS, Kubernetes, Keycloak, Vault, Git, GitLab CI/CD, IBM Cloud

Management Tools: OKR, Kanban, feedback loop, discovery and framing sessions, EPIC, Feature pitch
Python GO Bash DBT PostgreSQL Redis Kubernetes Git Gitlab CI/CD OKR Extraire, transformer, charger (ETL) Airflow
Veolia Water Technologies
GCP DATA ENGINEER
septembre 2019 - octobre 2022 (3 ans et 1 mois)
94410 Saint-Maurice, France
Hubgrade Digital Solutions, an initiative by Veolia Water Services, That aims to centralize all water related data to increase operational performance and water lifecycle management, detect production anomalies (water quality, waterleaks, management, etc.), and improve collaboration with stakeholders.

Data Warehouse Management: Maintained and optimized a 500+ TB BigQuery data warehouse, ensuring data availability and performance for decision-making.
Data Acquisition ETL / ELT Microservices: Designed and deployed dozens of scalable ETL microservices using Python, Flask, and Pandas on Google Cloud Engine and Cloud Functions.
Data Transformation Management: Developed and optimized an internal data transformation system (similar to dbt) orchestrated by Airflow to implement business rules and improve data quality.
FinOps Optimization and Monitoring: Implemented FinOps strategies, including user quotas, IAM management, and BigQuery query optimization, while monitoring GCP projects for resource efficiency and security.
ML Models deployment: Developing, Deploying and serving an ML model for predicting water consumption and estimating earning
Full-Stack Data Observability Solution: Built a strategic full-stack platform combining Python, Vue.js, and Firebase with machine learning (time series, clustering) to ensure data consistency, completeness, and proactive anomaly detection and alerting.

Tech Stack: Python, Bash, Java Script, Bitbucket, GCP, BigQuery, GCS, Pub/Sub, Compute Engine, Cloud Composer, Airflow, Looker

Management Tools: Scrum, KPI definition, Trust management, JIRA