Data Engineering
Helping organizations build reliable analytics platforms with Azure, Fabric, SQL Server and Power BI.
Build, review and optimize your ETL pipelines with over 10 years of experience working across the Microsoft ecosystem.
Reliable data pipelines are essential for delivering accurate reporting and supporting business decisions. Whether you're building a new platform, modernizing legacy processes or improving existing workloads, I can help design and implement solutions that are scalable, maintainable and cost-effective.
Typical Engagements
Technologies
Designing end-to-end data pipelines
Migrating legacy ETL workloads to Azure
Optimizing performance and reducing costs
Implementing monitoring and alert systems
Improving reliability and maintainability
Supporting analytics and reporting initiatives
Azure Data Factory
Microsoft Fabric
SQL Server
Python
Power BI
Web APIs
Cloud Architecture
Comprehensive reviews of existing architecture with recommendations covering performance, security and cost optimization, or bespoke designs tailored to your organization's requirements.
Modern cloud platforms must balance scalability, reliability and operational efficiency. Whether you're planning a migration, reviewing an existing environment or building a new platform from the ground up, I provide practical guidance based on real-world experience.
Typical Engagements
Areas of Expertise
Architecture reviews
Azure migration planning
Performance optimization
Cost management and resource sizing
Security and governance recommendations
Designing analytics and reporting platforms
Azure architecture
Microsoft Fabric
SQL Server
Data platform design
Security and governance
Cost optimization
Data Strategy Consulting
Technology alone does not create value. A successful data strategy requires the right architecture, governance and processes to support long-term business goals.
Creating a solid data foundation in the beginning is essential for success with AI and machine learning projects in the future.
Typical Engagements
Areas of Expertise
Data maturity assessments
Roadmap development
Platform modernization
Governance and ownership models
Reporting and analytics strategies
Technology selection
Database design
Data collection strategies
AI project planning
Standard Service Packages
Data Platform Health Check
Data Quality Assessment
Fractional Data Architect
Fixed scope architecture review
Identify risks and reliability gaps
Ongoing strategic and technical support
Pipelines
Databases
Infrastructure
Performance
Monitoring and Security
Areas included:
Outcomes:
Architecture overview
Performance insights
Quick fixes
Security recommendations
Areas included:
Pipeline reliability
Databases audit
Monitoring assessment
KPI design
Outcomes:
Data quality metrics
Quality improvement recommendations
Monitoring recommendations
Included:
Monthly support hours
Project work
Quick response