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# Data Engineer H/F

- **Company:** Groupe Klanik
- **Location:** Marseille, France
- **Experience:** Expert
- **Salary:** €40,000.0 - €45,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Databases, Continuous Integration, Data Governance, Extract Transform Load (ETL), Data Vault Modeling, Data Warehousing, DevOps, Python (Programming Language), Power BI, SQL Databases, SQLAlchemy, Azure Data Factory, Git, Microsoft Fabric
- **Published:** September 1, 2026
- **Apply:** https://www.hellowork.com/fr-fr/emplois/82886207.html

## About the Role

Microsoft Azure

 - Microsoft Fabric (OneLake, Data Factory, Data Warehouse, Power BI)
 - Python
 - SQL
 - Git / Azure DevOps
 - CI/CD pipelines
 - Power BI, Bac +5 en informatique, data ou équivalent- 3+ ans d'expérience en Data Engineering- Expérience significative sur Azure- Bonne maîtrise des concepts data (ETL, modélisation, data quality)- Expérience avec Microsoft Fabric (ou forte appétence)- Bonne maîtrise de SQL et Python- Esprit analytique et rigueur- Autonomie et proactivité- Bon relationnel et capacité à vulgariser- Esprit d'équipe, Bac +5 en informatique, data ou équivalent
 - 3+ ans d'expérience en Data Engineering
 - Expérience significative sur Azure
 - Bonne maîtrise des concepts data (ETL, modélisation, data quality)
 - Expérience avec Microsoft Fabric (ou forte appétence)
 - Bonne maîtrise de SQL et Python
 - Esprit analytique et rigueur
 - Autonomie et proactivité
 - Bon relationnel et capacité à vulgariser
 - Esprit d'équipe

EUR

Microsoft Azure
ETL
API
SQL
Modélisation des données
Power BI
Git
Pro-activité
Python
Autonomie
Esprit d'analyse

## Description

Concevoir, développer et maintenir des pipelines de données (ETL / ELT)

 - Intégrer des données provenant de sources multiples (API, bases de données, fichiers, etc.)
 - Mettre en place des architectures data modernes (Lakehouse, Data Warehouse)
 - Exploiter et optimiser les services Azure Data (Data Factory, Synapse, Fabric...)
 - Participer à la modélisation des données (modèles en étoile, data vault, etc.)
 - Garantir la qualité, la fiabilité et la gouvernance des données
 - Collaborer avec les équipes Data Science, BI et métiers
 - Mettre en place des bonnes pratiques DevOps (CI/CD, monitoring, automatisation)
 - Assurer la documentation technique


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