Freelancer profile translated to English.

Description

Does yourdata infrastructurecost more than it generates revenue, or does your team spend hourson tasksthat should be **automated**?

You need aData Engineerwho doesn't just deliver code for code's sake: everydata pipeline**, every **lakehousearchitecture, everyautomationis designed to serve a measurable **business objective**.

My obsession: theROIof every project.

Here's what my clients have concretely achieved:

Chanel**: Implementation of a **custompayloadgenerator+ completeautomationof theQAtesting cycle.80%+of time recovered on **repetitive tasks**, zero residual manual tasks.
CarbonArc**: Reconstruction of stable **PySparkclusters +optimizationofSpark**-**Icebergpipelines.-80%of files processed unnecessarily,-90%ofmaintenancetime, daily losses of severalthousands of dollarsstopped.
Energy Sector**: **Cloud audit+automationof 20+ hours of weeklymanual processing**. Cloud **billof $5,000 → less than $1,000/month, $48,000 **saved**/year.

Present your **business problem**, I will identify value leaks and propose a suitable **data ROADMAP**.

I work with startups, SMEs, and large corporations inall sectors**, on **Big Dataprojects,lakehousearchitecture, andworkflow**automation**.

Do you have a project or adata initiativein mind?

Describe your situation in 3 lines, I will respond within the hour with an initial assessment of your needs.

You can also reach me on WhatsApp:

Industry field of expertise

Languages

English
Native or bilingual
French
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km), Lyon (up to 50km), Bordeaux (up to 50km), Nice (up to 50km), Rennes (up to 50km)

L'Oréal
Data Engineer
FASHION AND COSMETICS
October 2024 - Today (1 year and 10 months)
Levallois-Perret, France
Complete redesign of a data platform that had become complex and costly.
In detail:
• Agile team (10 devs, 1 PO, 1 Scrum Master)
• Migration from a heterogeneous architecture (10+ technologies) to a modern, clear, and standardized stack
• Design of a Lakehouse MVP: Airflow (orchestration), Spark (processing), Delta Lake (storage), Grafana (DataViz)
• Deployment on Azure Kubernetes (AKS) with automated DevOps infrastructure and CI/CD
• Integration of 35+ data sources and creation of scalable pipelines
• Technical workshops, pair programming, training, recruitment of data engineers
• Production deployment validated

Technical stack:
Python, Airflow, PySpark, Delta, Azure, Docker, Github Actions, K8s, PostgreSQL, Jupyter Notebook, Elasticsearch, Grafana
Python Airflow PySpark Delta Lake Lakehouse
PulseChk
Data Engineer
CONSULTING AND AUDITS
October 2024 - Today (1 year and 10 months)
United States
In detail:
• Complete diagnosis of the existing platform and identification of performance bottlenecks
• Optimization of critical Spark processing to reduce computation times and execution costs
• Redesign of the batch processing strategy with better scalability management
Architecture Spark SQL Lakehouse Big Data
Carbon Arc
Data Engineer
TECH
December 2024 - February 2025 (2 months)
New York, NY, USA
Urgent mission to regain control of an unstable and costly Spark platform.
• Agile team (2 devs, 1 Head of Eng)
• Complete audit of Spark workflows on Domino: detection of cost leaks related to autoscaler
• Proposal of a rapid solution to ensure reliable execution and stabilize costs
• Optimization of the Apache Iceberg format: -80% of files generated (faster and cheaper spark jobs)
• 90% reduction in maintenance time over several Terabytes of data
• Mentoring and support for internal teams
• Weekly technical reporting to the Head of Eng

Technical Environment:
- AWS, Domino Lab Platform, Python, PySpark, Airflow, Apache Iceberg, Github, Trino
AWS S3 Python Spark Apache Iceberg Airflow