Freelancer profile translated to English.
Back to original languageAbout Yvan
Looking to make your data pipelines more reliable or accelerate your migration to a Modern Data Stack / Fabric? .
With 5 years of experience as a Senior Data Engineer, I assist Data departments (Luxury, Banking, Health) in industrializing their cloud data architectures. Myrole**: **transforming your raw data into scalable, secure, and exploitable assets, from ingestion to visualization
What I bring you concretely:
- Azure & Fabric Expertise : Design of modern architectures (Synapse, ADF, Data Lakehouse) and large-scale data processing with PySpark.
- Modern Data Stack (MDS) : Mastery of transformation tools like dbt to ensure clean, documented data ready for analysis.
- Industrial Rigor : Complete automation of production deployment cycles (CI/CD) and containerization via Docker.
- Visualization & Analytics : Design of complex Power BI dashboards to translate technical data into actionable business insights.
My added value :
I don't just "push code". At SMCP (Luxury), I reduced deployment errors by 50%. At Sevetys, I orchestrated end-to-end ingestion and visualization to ensure operational continuity.
My typical interventions :
✅ Migration & Big Data : Transition to Azure Fabric and optimization of processing via PySpark / Databricks.
✅ Industrialization & DevOps : Setup of CI/CD pipelines (GitLab/GitHub) and Docker containerization.
✅ ETL/ELT Development : Complex pipelines in Python and modeling via dbt.
✅ End-to-End Reporting : Creation of KRIs and detailed Power BI reports for strategic management.
Based in Puteaux / La Défense, I am immediately available to discuss your challenges, whether in hybrid or remote mode.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km)
Experience
- QuintetSenior Data Engineer Azure Freelance - Governance & Risk Management (Banking Sector)BANKING AND INSURANCEMarch 2026 - April 2026 (1 month)Luxembourg, LuxembourgThe challenge: Centralize critical data flows and automate the monitoring of risk indicators (KRI) to meet the regulatory and strategic requirements of a financial institution.Key achievements:
- Analytics Architecture on Azure Synapse : Design and implementation of optimized datasets within Synapse, enabling the processing of massive volumes of financial data with high availability.
- Creation of Semantic Models : Development of robust semantic layers to unify business definitions. Establishment of a "Single Source of Truth" facilitating data access for business departments.
- Automation of Business KRIs : Translation of complex business rules into automated Key Risk Indicators, reducing regulatory reporting times.
- Performance Optimization : Tuning of complex SQL queries and data structuring to ensure ultra-fast response times on data models.
Technical Stack : Azure Synapse Analytics, SQL, Semantic Modeling, Power BI (DAX), Azure Data Lake Storage (ADLS). - Sevetys,Senior Data Engineer - Architecture & Data Modernization (Health Sector)HEALTH AND WELLNESSMarch 2025 - December 2025 (9 months)Paris, FranceThe challenge: Synchronize and make critical data flows (patients, appointments, health) reliable and manage the performance of a rapidly growing clinic network.Key achievements:
- Performance Management (BI): Design and deployment of complexPower BIdashboards for the Performance team. Implementation of management indicators (financial and operational KPIs) for real-time monitoring of clinic activities.
- Industrialization of "Clinic Onboarding": Complete automation of data migrations during clinic acquisitions, ensuring 24/7 service continuity and total patient data integrity.
- Analytics Architecture (Star Schema): Modeling and centralization of CRM and Marketing data on Azure Synapse (star architecture) for granular customer behavior analysis.
- Relational Marketing Engine: Development of daily automated ETL/ELT pipelines for customer follow-ups (vaccines, reminders), significantly increasing campaign conversion rates.
- Big Data & API Processing : Use of PySpark for processing massive volumes and FastAPI for interoperability between health systems.
Technical Stack : Azure Data Factory (ADF), Synapse, Power BI (DAX), PySpark, Python, FastAPI, SQL, PostgreSQL. - SollywoodCloud Data Engineer & Solutions Architect - End-to-End Data StrategyFILM AND AVFebruary 2024 - March 2025 (1 year and 1 month)Puteaux, FranceThe challenge: Design and deploy a complete data and application infrastructure on Azure to transform raw data (YouTube) into a scalable analytics platform.Key achievements:
- Mass Ingestion & Scraping**: Design of an automated scraping engine using Python (Selenium) for collecting video metadata, with optimized storage on Azure Blob Storage and structuring in MySQL. Then, implementation of **Fabric / Onelake.
- **Automation & Performance Gain**: Workflow orchestration via Azure Data Factory (ADF) and Python Notebooks. Result: -30% processing time and a 25% reduction in errors due to the implementation of validation and cleaning pipelines.
- **Analytics & BI**: Data exploration via SQL/Python and creation of interactive dashboards in Power BI, providing real-time visibility into content performance.
- Cloud Deployment(Fullstack): Production deployment of the application (Node.js Backend / React Frontend) on Azure App Service, ensuring the solution's high availability and scalability.
Technical Stack: Azure (ADF, Blob Storage, SQL DB, App Service), Fabric, Python (Selenium), SQL, Power BI, Node.js, React.
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Education
- Engineering Diploma in Information Systems (specialization Big Data & AI)ECE(Ecole Centrale d'Electronique)2021Diplôme d'Ingénieur en
- Azure FundamentalsMicrosoft2024Azure Fundamentals