Fabric Data Engineer: Build Scalable Pipelines & Analytics

Dynatechconsultancy

United Kingdom

Remote

GBP 60,000 - 80,000

Full time

7 days ago
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Job summary

Dynatechconsultancy is seeking a Microsoft Fabric Data Engineer to design and manage data pipelines and analytics platforms, working with architects and business teams to ensure reliable, high-performance data processing and reporting. Design and build pipelines with Microsoft Fabric, develop data transformation workflows, and ensure data quality and consistency across systems for accurate reporting.

Collaborate with analytics teams, optimize pipeline performance, maintain documentation, and

Qualifications

  • Experience with Microsoft Fabric or similar data platforms.
  • ETL/ELT pipeline development experience.
  • Experience with large datasets and distributed systems.
  • Strong analytical and problem-solving abilities.
  • Ability to collaborate with cross-functional teams.

Responsibilities

  • Design and build data pipelines using Microsoft Fabric.
  • Develop data transformation and processing workflows.
  • Ensure data quality, consistency, and reliability across systems.
  • Collaborate with analytics teams to support reporting requirements.
  • Optimize performance of data pipelines and storage systems.
  • Monitor and troubleshoot data-related issues.
  • Maintain documentation for data processes and workflows.
  • Stay updated with Microsoft Fabric features and enhancements.

Skills

Microsoft Fabric
ETL/ELT pipelines
Large datasets
Analytical skills
Cross-functional collaboration

Education

Bachelor’s degree in Computer Science, Data Engineering, or related field

Tools

Power BI
Azure data services

Job description

Dynatechconsultancy is seeking a Microsoft Fabric Data Engineer to design and manage data pipelines and analytics platforms, working with architects and business teams to ensure reliable, high-performance data processing and reporting. Design and build pipelines with Microsoft Fabric, develop data transformation workflows, and ensure data quality and consistency across systems for accurate reporting.

Collaborate with analytics teams, optimize pipeline performance, maintain documentation, and

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