Microsoft Data Engineer Consultant at Magellan Partners

Meylan, Auvergne-Rhone-Alpes, France -

Full Time

Start Date

Immediate

Expiry Date

31 Aug, 26

Salary

0.0

Posted On

02 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure Data Factory, Azure Fabric, Azure Synapse, SQL, MySQL, Power BI, ETL/ELT, Data Lake, Data Warehouse, Lakehouse, DevOps, DataOps, Data Modeling, Cloud Infrastructure, English, French

Industry

Business Consulting and Services

Description

Company Description Ready to turn vision into action? Magellan is an international Management and Technology Consulting Group. Our strength lies in our ability to combine business expertise and technological excellence to support companies and public organizations throughout their transformation journeys. VISION IN ACTION In an environment where change is accelerating, organizations must continuously reinvent their models to remain competitive. To address these challenges, we support our clients from strategy definition through operational implementation, combining business expertise, technological mastery, and execution capabilities. Joining Magellan means becoming part of a community of 6,700 committed professionals united by a shared ambition: understanding challenges in all their complexity to build practical, actionable solutions that are closely aligned with real-world needs. Job Description The industrialisation of Data platforms on the Microsoft Azure ecosystem (Data Lake, Data Warehouse, Lakehouse, ETL/ELT pipelines, Power BI) is a strategic undertaking for data-driven organisations. This role, with 3 days per week in Lyon, is aimed at an experienced Microsoft Data Engineer, autonomous on large-scale projects potentially spanning several hundred days. 💡 YOUR MISSIONS As a Microsoft Data Engineer Consultant (M/F), you play a central role in the design, structuring, and go-live of our clients' data platforms. Travel to Lyon 3 days per week is required. Participate in defining and implementing clients' Data & Cloud strategy Analyse business requirements, scope data quality, volume, and performance challenges Implement data ingestion, transformation, and processing pipelines (batch & 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 performant data models Collaborate with BI teams to feed reporting tools (Power BI, etc.) Ensure data quality, consistency, and security across the entire data 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 Qualifications 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 is a plus. 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) as speaking French fluently. Additional Information By joining Magellan, you will work within multidisciplinary teams and contribute to impactful projects at the heart of major transformations: Generative AI, intelligent platforms, social and environmental challenges, and more. What Magellan guarantees you: a professional experience that is people-centered, enriching, and fulfilling! Agence: GRENOBLE

Responsibilities

Design and implement data platforms on the Microsoft Azure ecosystem, including the creation of ingestion and transformation pipelines. Collaborate with BI teams and clients to define data strategies and ensure data quality and security.