Data Architect with Fabric

Solution Architecture & Design
Lead end-to-end architecture and implementation of Microsoft Fabric solutions.
Design scalable, secure, and high-performing enterprise data platforms.
Develop data architecture standards, best practices, and governance frameworks.
Create enterprise data models, data lakehouse architectures, and semantic layer strategies.
Provide technical leadership for large-scale data transformation initiatives.
Establish architecture roadmaps aligned to business objectives and digital transformation strategies.
Microsoft Fabric Platform Leadership
Architect and implement solutions utilizing:
Fabric Data Factory
Fabric Data Engineering
Fabric Data Warehouse
Fabric Lakehouse
Fabric Real-Time Analytics
Fabric Data Science
Fabric Power BI
OneLake
Copilot in Fabric
Optimize workloads for scalability, performance, and cost efficiency.
Lead Fabric adoption and modernization programs.
Data Engineering & Integration
Design and oversee enterprise ETL/ELT frameworks.
Build and optimize data ingestion, transformation, and orchestration pipelines.
Integrate structured, semi-structured, and unstructured data sources.
Develop data migration strategies from legacy platforms to Microsoft Fabric.
Implement data quality, validation, and reconciliation processes.
Analytics & Reporting
Define enterprise reporting and analytics architectures.
Design semantic models and business-friendly data marts.
Enable self-service BI through Power BI and Fabric.
Establish KPI frameworks, executive dashboards, and enterprise reporting standards.
Optimize data models and reporting performance.
Technical Leadership
Lead and mentor teams of Data Engineers, BI Developers, Data Analysts, and Data Scientists.
Conduct architecture reviews and code reviews.
Define development standards and engineering best practices.
Drive Agile delivery and technical governance activities.
Act as the primary technical escalation point for complex Fabric solutions.
Data Governance & Security
Implement enterprise data governance frameworks.
Define metadata management and data lineage strategies.
Ensure regulatory and compliance requirements are met.
Implement security controls, role-based access, and data protection policies.
Support audit and regulatory requirements.