Freelancer profile translated to English.

Description

Tech Lead Data Engineer with 5 years of experience on high-stakes data platforms (large retail, luxury, automotive, industry accounts).

Specialized in Microsoft Fabric since its inception: Eventhouse, KQL,

Lakehouse, Data Factory, Warehouse, OneLake.

🎯 What I do concretely:

- Design and industrialization of batch and streaming ingestion frameworks

(PySpark, KQL, Real-Time Intelligence)

- Medallion Architecture, Lakehouse / Warehouse, reusable multi-client models

- Implementation of complete CI/CD (Azure DevOps, Terraform, GitLab)

- Tech leadership: standards, architecture reviews, Fabric best practices, team upskilling

- On-premise → Fabric / Azure / GCP migration

🏆 Some achievements:

- End-to-end RTI streaming ingestion framework delivered in less than 4 months for a European B2B distribution leader

- Global PySpark batch backbone deployed for a luxury player (Lakehouse + Medallion, multi-entity)

- Cloud Data Fabric platform for the modernization of a large industrial's on-premise ecosystem

- GCP Connected Car Platform (BigQuery, Dataflow, Pub/Sub) for an automotive manufacturer

🛠 Stack mastered:

Microsoft Fabric (Eventhouse, KQL DB, Update Policies, Data Factory,

Warehouse, Lakehouse, Notebooks, Direct Lake), PySpark, Python, SQL,

KQL / Kusto, Databricks, Azure, GCP (BigQuery, Dataflow, Pub/Sub),

Terraform, Azure DevOps, Docker.

📜 Certified: DP-203 Azure Data Engineer, Fabric Data Engineer (DP-700),

Databricks Professional, GCP Professional Data Engineer.

Available for missions: audit / POC Fabric, ingestion framework implementation, architecture & scoping, real-time streaming expertise (KQL / Eventhouse), data team training / mentoring.

Fluent English (TOEIC 900). Based in Paris, open to remote and hybrid.

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Remote only

Primarily works remotely

Chanel
Tech Lead Data Engineer
October 2025 - Today (8 months)
Tech lead on the evolution of the Chanel Data Platform, covering batch and real-time workloads on Microsoft Fabric.

- Technical leadership on ingestion, DevOps, Fabric components, and real-time streaming (Eventhouse, KQL Databases, Update Policies)
- Development of batch and RTI ingestion pipelines
- Design of reusable frameworks (batch + streaming)
- DevOps ownership: CI/CD, automation, observability, platform reliability
- Cross-functional team support on architecture, ingestion patterns, and Fabric best practices

Stack: Microsoft Fabric, Eventhouse, KQL, PySpark, Azure DevOps, Terraform, Python, SQL
Microsoft Fabric Python KQL RTI
SAINT-GOBAIN
Lead Data Engineer
MECHANICAL ENGINEERING
June 2025 - October 2025 (4 months)
Paris, France
Modernization of the on-premise data ecosystem through the construction of a Cloud Data Platform on Microsoft Fabric.

- Architecture and development of the SQL analytics framework and the Fabric ingestion framework
- Automation of dynamic pipelines and Warehouse / Lakehouse ingestion patterns
- End-to-end development, testing, monitoring, and maintenance of flows
- Standardization of Fabric patterns, Medallion architecture, and reusable components
- Co-authoring of the architecture blueprint with the Data Architect

Stack: Microsoft Fabric, Data Factory, Warehouse, Lakehouse, SQL, PySpark, Medallion Architecture, Azure DevOps
Microsoft Fabric SQL Data Warehouse Lakehouse
CHANEL
Lead Data Engineer Fabric / DevOps
LUXURY GOODS
March 2023 - September 2024 (1 year and 6 months)
Paris, France
Construction of the global Chanel Data Platform's centralized batch ingestion backbone.

- End-to-end ownership of the dynamic PySpark ingestion framework: automated ingestion, Lakehouse, Medallion architecture across all business entities
- Development and maintenance of Microsoft Fabric ETL pipelines (PySpark, SQL, Notebooks)
- Co-design of the architecture with the Data Architect (data models, platform standards)
- Implementation of complete CI/CD with Azure DevOps + Terraform
- Development of Purview integration flows (Azure Functions, .NET Function App)

Stack: Microsoft Fabric, PySpark, Lakehouse, Medallion, Azure DevOps, Terraform, Purview, Azure Functions, .NET
Data Engineering Microsoft Azure Data architecture Microsoft Fabric Python