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# AI Data Scientist Consultant (M/F)

- **Company:** Magellan
- **Location:** Valbonne, France (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Databases, Data as a Services, Extract Transform Load (ETL), Data Security, Data Warehousing, DevOps, MySQL, Power BI, DataOps, SQL Databases, Data Storage Technologies, Data Ingestion, Azure Data Factory, Data Lakes, Integration Frameworks, Data Management, Tools for Reporting, GPT, Data Pipelines
- **Published:** September 1, 2026
- **Apply:** https://fr.indeed.com/viewjob?jk=c652b945fee0170a

## About the Role

* Good knowledge of the Azure platform as a whole and its associated ecosystem. DATA services in Azure (DataFactory, Azure Fabric, Synapse, etc.). Databases (SQL, MySQL).
 * Data storage and processing challenges in Azure (Storage Account, Data Lake Store, Data Factory, Logic App).
 * Data security in Azure. Knowledge of IoT and AI data management in Azure.
 * With a Master's degree (Bac+5), you have at least 3 years of significant experience in cloud IT infrastructure, particularly on the Azure platform.
 * A strong communicator with excellent writing skills, you are able to adapt to both teamwork and client projects.
 * Good command of English is mandatory (reading, writing, speaking)., Early access to new technologies such as #M'GPT, #Copilot, and the highest levels of Microsoft certifications!

## Description

As an AI Data Scientist Consultant (M/F), you play a central role in the design, structuring and go-live of our clients' data platforms.

 * Participate in defining and implementing clients' Data & Cloud strategy
 * Analyse business needs, scope data quality, volume and performance challenges
 * Implement data ingestion, transformation and processing pipelines (batch and real-time)
 * Build and optimise Data Lake, Data Warehouse or Lakehouse environments following architectural recommendations
 * Industrialise ETL/ELT workflows following DevOps/DataOps best practices
 * Implement reliable and high-performance data models
 * Collaborate with BI teams to feed reporting tools (Power BI)
 * Ensure data quality, consistency and security across the entire chain
 * Participate in workshops with business and IT teams
 * Contribute to technical scoping, pre-sales and client demonstrations
 * Draft technical documentation (HLD, LLD, operations manuals)
 * Maintain a watch on the Azure Data ecosystem, data processing frameworks and DataOps tools


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