Overview:
We are seeking a highly skilled Fabric Architect to design, implement, and optimize data architecture and pipelines across the Microsoft Fabric ecosystem. This role requires a strategic thinker with deep technical expertise in data modeling, ingestion frameworks, and environment configuration. You will play a key role in building a robust data platform from source ingestion through to curated, high-value datasets, enabling actionable insights and scalable analytics. This is a hands-on architecture role that balances technical design with implementation, governance, and performance optimization.
Location: Across Canada & USA
Status: Contract or Full-Time

QUALIFICATIONS, SKILLS & EXPERIENCE:

• Proven experience architecting and implementing solutions on Microsoft Fabric
• Strong understanding of data lakehouse architecture principles (Bronze/Silver/Gold layers)
• Proficiency in Data Factory, Dataflows, Pipelines, and Power Query (M) and T-SQL/DAX
• Hands-on experience with data modeling, including fact and dimension design
• Demonstrated expertise in building source-to-target mappings, ETL/ELT processes, and pipeline orchestration
• Familiarity with hybrid connectivity setups, including on-premise gateway installation and configuration
• Experience in setting up and managing multi-environment workspaces with deployment and naming standards
• Strong problem-solving skills with attention to data quality, performance, and reusability
• Excellent communication and documentation abilities

• Workspace Design & Governance
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• Define and implement workspace design and naming standards in Microsoft Fabric

• Set up and manage separate Fabric workspaces for Development, QA/Test, and Production environments
• Infrastructure & Integration
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• Support the installation and configuration of the Fabric Gateway on on-premise virtual machines to enable secure hybrid data connectivity

• Data Architecture
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• Design and implement the Gold Layer data model within Microsoft Fabric, including:

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• 1 comprehensive Data Mart

• 1 Fact Table (up to 15 attributes)
• Up to 5 related Dimension Tables
• Develop and maintain a Source-to-Target Mapping Document to ensure traceability and lineage
• Data Engineering & Pipelines
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• Implement a reusable, scalable data ingestion framework for the Bronze Layer

• Ingest data from up to 15 diverse source tables (average 15 attributes each) into the Bronze Layer
• Design and implement Bronze-to-Silver pipelines using primary key-based merging for consistency across all 15 tables
• Build transformation logic to process Silver Layer data into the Gold Layer, optimizing for analytics consumption