MSH
Fabric Analytics Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Fabric Analytics Engineer, offering a contract of unspecified length at a pay rate of "unknown." Key skills include Microsoft Fabric, Power BI, DAX, and experience in data quality and governance.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 12, 2025
🕒 - 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
Los Angeles, CA
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🧠 - Skills detailed
#Datasets #DAX #Data Accuracy #Microsoft Power BI #BI (Business Intelligence) #Data Quality #Semantic Models #Documentation #Data Engineering
Role description
Role Summary:
Designs and delivers business intelligence solutions, semantic models, governed
datasets, dashboards, KPIs, and analytics using Microsoft Fabric and Power BI.
Key Responsibilities:
• Design and build semantic models using Direct Lake, Import, and Composite modes.
• Develop dashboards, reports, scorecards, and governed enterprise datasets.
• Create DAX measures, KPIs, time intelligence logic, and role-based perspectives.
• Implement governance: RLS/OLS, certifications, endorsements, sensitivity labels.
• Perform performance tuning, DAX optimization, query reduction, and refresh optimization.
• Validate report outputs, reconcile with source systems, and resolve data quality issues.
• Manage workspace lifecycle, dataset refresh scheduling, and workspace hygiene.
• Provide documentation, visual standards, user training, demos, and enablement support.
• Maintain existing BI content and support enhancements based on business needs.
• Collaborate with Data Engineers to ensure data accuracy and semantic alignment.
Role Summary:
Designs and delivers business intelligence solutions, semantic models, governed
datasets, dashboards, KPIs, and analytics using Microsoft Fabric and Power BI.
Key Responsibilities:
• Design and build semantic models using Direct Lake, Import, and Composite modes.
• Develop dashboards, reports, scorecards, and governed enterprise datasets.
• Create DAX measures, KPIs, time intelligence logic, and role-based perspectives.
• Implement governance: RLS/OLS, certifications, endorsements, sensitivity labels.
• Perform performance tuning, DAX optimization, query reduction, and refresh optimization.
• Validate report outputs, reconcile with source systems, and resolve data quality issues.
• Manage workspace lifecycle, dataset refresh scheduling, and workspace hygiene.
• Provide documentation, visual standards, user training, demos, and enablement support.
• Maintain existing BI content and support enhancements based on business needs.
• Collaborate with Data Engineers to ensure data accuracy and semantic alignment.
