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Microsoft Fabric Engineer

E-Solutions · Abidjan

Nouveau
Senior 🇬🇧 English
Microsoft Fabric OneLake Lakehouse Data Pipelines Notebooks Data Warehouses Semantic Models Power BI PySpark Spark SQL SQL Python Medallion Architecture Azure DevOps Git CI/CD Data governance Metadata management Azure Data Services

Description du poste

About the role

We are seeking a Microsoft Fabric Engineer to design, develop, and support modern data and analytics solutions on the Microsoft Fabric platform for a banking client. The role involves building scalable data pipelines, implementing Lakehouse architectures, and delivering business intelligence using Power BI. The position is based in Abidjan with a hybrid work arrangement (three days onsite per week).

Key responsibilities

  • Develop and maintain data solutions using Fabric components such as OneLake, Lakehouse, Data Pipelines, Notebooks, Data Warehouses, and Semantic Models.
  • Design and optimise ETL/ELT processes, applying Medallion Architecture (Bronze, Silver, Gold) to ensure data quality and lineage.
  • Configure and manage Fabric workspaces, implement security controls, and integrate data from cloud, on‑premises, and third‑party sources.
  • Implement CI/CD pipelines with Azure DevOps and Git, automate deployments, and monitor platform performance.
  • Collaborate with architects, analysts, data scientists, and reporting teams to translate business requirements into scalable solutions.

Required profile

  • 7‑10+ years of experience in data engineering and analytics, preferably within banking or large enterprises.
  • Strong analytical, problem‑solving, and communication skills, with the ability to work independently and in cross‑functional teams.
  • Demonstrated focus on quality, delivery excellence, and continuous improvement.

Required skills

  • Microsoft Fabric (OneLake, Lakehouse, Data Pipelines, Notebooks, Data Warehouses, Semantic Models)
  • Power BI datasets and report development
  • PySpark, Spark SQL, SQL, Python
  • Medallion Architecture and modern data platform patterns
  • Azure DevOps, Git, CI/CD practices
  • Data governance, security, and metadata management
  • Azure Data Services and cloud‑native analytics platforms

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