Summary
✨ AI‑Generated
Design and build reliable, scalable data platforms while guiding organizations through modern analytics transformations. You will take a leading role in Microsoft Fabric, working across architecture, engineering, analytics, and governance to create well-designed cloud-native data environments. The position combines deep technical work with practical client guidance and internal knowledge sharing.
Highlights
Advanced data engineering role combining architecture, engineering, analytics, governance, and client advisory work, with a leading position in Microsoft Fabric and opportunities to shape modern data platforms.
Description
At Xebia Microsoft Services (XMS), we help organizations turn their data ambitions into reality through modern engineering, thoughtful architecture, and deep Microsoft expertise.
As a Data Engineer, you design and build the data solutions that make this possible.
You bring clarity to complex environments, guide clients as they adopt Microsoft Fabric, and support teams in working effectively with cloud-native analytics.
Join us and help shape the next generation of data platforms.
Responsabilities As a Data Engineer, you help clients turn their data ambitions into reliable, scalable data platforms.
Within this role, you will also take a leading position in Microsoft Fabric, guiding both clients and internal teams in adopting and implementing Fabric as a modern data platform.
You work across architecture, engineering, analytics, and governance, bringing technical depth and practical guidance to every stage of the engagement.
You ensure that platforms built on Fabric are well-designed, maintainable, and ready to support real business value.
In practice, this means: Solution Design & Architecture: Designing end-to-end data architectures using Microsoft Fabric (Lakehouse, Data Engineering, Data Factory, Real-Time Analytics, Power BI).
Data Engineering: Building and optimizing data pipelines and notebooks using Spark, Dataflows Gen2, Pipelines, and ELT/ETL best practices.
Data Governance: Defining governance frameworks: domains, workspaces, OneLake structures, cataloging, lineage, and security.
Analytics & BI Enablement: Creating high-quality semantic models and datasets that empower BI teams, and real-time analytics use cases.
Azure Integration: Integrating Fabric with broader Azure services such as ADLS, Event Hub, Azure SQL, Databricks, and Purview.
Stakeholder Enablement: Guiding stakeholders through Fabric adoption with workshops, assessments, PoCs, and knowledge transfer.
