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Microsoft Fabric Expert

8 years

0 Lacs

India

Posted:1 month ago| Platform: Linkedin logo

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Skills Required

engagement data architecture support analytics pipeline orchestration azure design integration etl strategies power migrate sql reports monitoring automation governance ai logic vault api python technology spark

Work Mode

On-site

Job Type

Full Time

Job Description

Microsoft Fabric expert

Key Responsibilities:

  • Azure Data Factory:

     Design and manage robust data integration solutions, including ETL/ELT pipelines and data movement strategies by leveraging the unified capabilities of Azure Data Factory and Power Query.
  • Migrate existing SQL data structures, DBs to 

    Microsoft Fabric

  • Power BI

     Design and implement interactive reports and dashboards. Leverage 

    DirectLake

     mode to enable high-performance queries against Delta Lake tables in OneLake without data duplication.

  • Data Activator

     Implement real-time data monitoring and event-driven automation by setting up triggers based on data patterns from OneLake or Power BI visualizations.
  • Experience integrating 

    Microsoft Purview

     for governance and compliance.
  • Solid understanding of medallion architecture for 

    AI optimization

    .
  • Understanding of 

    Azure Logic Apps

    , Azure Functions, Key Vault and API Management
  • Strong knowledge of Python, notebooks, and data modeling concepts.

 

Required Skills and Experience:

  • Minimum 8 + years technology experience , preferably in the Microsoft space
  • Proven experience in designing enterprise-scale data architectures using Microsoft Fabric
  • 5 + years experience of Azure Synapse
  • Deep understanding of Microsoft Fabric ecosystem.
  • 5 + years experience of ETL/ELT tools, Spark, KQL, and SQL-based data warehousing.
  • 5 + years experience with Power BI, particularly DirectLake capabilities.
  • Good working knowledge with real-time data analytics and event-based systems.
  • Ability to collaborate with data engineers, data scientists, and business stakeholders.

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