

Vector Resourcing
Fabric Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Fabric Data Engineer on a contract basis, focusing on Microsoft Azure. Key skills include PySpark, SQL, and API integration. Responsibilities involve building data pipelines, ensuring data quality, and automating infrastructure with Bicep.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
May 13, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Deployment #Microsoft Azure #Logging #API (Application Programming Interface) #Documentation #Data Pipeline #Data Architecture #Spark (Apache Spark) #Scala #"ETL (Extract #Transform #Load)" #Data Processing #Azure SQL Database #Monitoring #Azure SQL #Azure #SQL (Structured Query Language) #Data Quality #PySpark #Data Engineering
Role description
We are searching for a hands-on Data Engineer who will deliver high-quality, scalable data solutions across our client's Microsoft Azure ecosystem. This role involves building robust data pipelines within Microsoft Fabric, integrating external systems via APIs, and designing data flows aligned to the Medallion architecture to support analytics, integration, and reporting requirements.
Responsibilities
• Build and maintain data pipelines using Microsoft Fabric Data Factory, supporting database-based, file-based and API-based ingestion, transformation and orchestration
• Develop scalable data processing logic using PySpark and SQL for both Lakehouse and Warehouse workloads
• Design and implement data solutions aligned to the Medallion architecture (Bronze, Silver, Gold layers) to support analytics and reporting requirements
• Integrate external systems through secure and reliable API calls
• Ensure operational visibility across pipelines, including robust logging, monitoring and error-handling mechanisms
• Work with Azure SQL Database, OneLake and Lakehouse components to deliver efficient ingestion and transformation processes
• Automate infrastructure provisioning and configuration using Bicep (Infrastructure-as-Code)
• Contribute to and enhance CI/CD pipelines to enable automated deployment across Fabric workspaces and Azure environments
• Troubleshoot pipeline failures, resolve performance bottlenecks and address data quality issues
• Collaborate closely with data architects, analysts and engineering teams to deliver high-quality, production-ready data solutions
• Maintain comprehensive technical documentation, pipeline runbooks and governance guidelines
We are searching for a hands-on Data Engineer who will deliver high-quality, scalable data solutions across our client's Microsoft Azure ecosystem. This role involves building robust data pipelines within Microsoft Fabric, integrating external systems via APIs, and designing data flows aligned to the Medallion architecture to support analytics, integration, and reporting requirements.
Responsibilities
• Build and maintain data pipelines using Microsoft Fabric Data Factory, supporting database-based, file-based and API-based ingestion, transformation and orchestration
• Develop scalable data processing logic using PySpark and SQL for both Lakehouse and Warehouse workloads
• Design and implement data solutions aligned to the Medallion architecture (Bronze, Silver, Gold layers) to support analytics and reporting requirements
• Integrate external systems through secure and reliable API calls
• Ensure operational visibility across pipelines, including robust logging, monitoring and error-handling mechanisms
• Work with Azure SQL Database, OneLake and Lakehouse components to deliver efficient ingestion and transformation processes
• Automate infrastructure provisioning and configuration using Bicep (Infrastructure-as-Code)
• Contribute to and enhance CI/CD pipelines to enable automated deployment across Fabric workspaces and Azure environments
• Troubleshoot pipeline failures, resolve performance bottlenecks and address data quality issues
• Collaborate closely with data architects, analysts and engineering teams to deliver high-quality, production-ready data solutions
• Maintain comprehensive technical documentation, pipeline runbooks and governance guidelines






