Background:

I architect enterprise-scale data platforms that drive digital transformation and measurable business value.

Cloud & Data Architect with 10+ years delivering strategic solutions for government and Fortune 500 clients. I specialize in designing federated data ecosystems, implementing AI/ML services, and leading enterprise modernization initiatives. My work spans cross-ministry data platforms, actuarial valuation systems processing 500+ terabytes, and nationwide infrastructure planning solutions—consistently delivering cost optimization, operational efficiency, and scalable architectures that align technical execution with strategic objectives.

Key Achievements:

• $3.8M Infrastructure Optimization: Designed serverless architecture reducing operational costs while improving scalability and reliability for enterprise workloads.
• $160K Monthly Savings: Led cloud migration strategy and resource optimization, delivering sustained cost reduction through architectural improvements.
• Enterprise-Scale Data Platform: Architected global actuarial valuation pipeline managing $100M infrastructure, 5000+ VMs, and 500TB of data with dynamic scaling capabilities.
• Cross-Ministry Data Ecosystem: Designed federated data sharing platform supporting AI/ML services across multiple government organizations.
• 50% Capacity Enhancement: Implemented infrastructure-as-code automation increasing computational efficiency within six months.
• Operational Efficiency: Automated critical business processes saving 2500+ hours weekly through intelligent workflow design.

Core Competencies:

Professional Experience:

Leading enterprise data modernization initiatives for government and Fortune 500 clients, delivering strategic data platforms and AI-enabled services.

Select Client Projects:

• Manulife (4 years): Designed and implemented global actuarial valuation pipeline managing $100M infrastructure, 5000+ VMs, and 500TB of data. Architected mainframe-to-cloud-to-dashboard pipelines with dynamic scaling and load balancing. Integrated NLP models for sentiment analysis in ETL workflows and developed agentic workflows to automate repetitive tasks.

• Federal, Alberta, BC Governments (via PWC, 1 year): Designed federated data ecosystem architecture supporting cross-ministry data sharing and AI/ML services. Led strategic planning sessions with C-suite executives to develop data strategy roadmaps aligned with digital transformation goals. Established DevSecOps practices and CI/CD pipelines for secure, automated deployment.

• Telus Mobility (2 years): Architected Canada-wide 5G spectrum planning solution with $1M infrastructure using Kubernetes-based distributed Python microservices. Built data pipelines integrating government ArcGIS maps with analytical dashboards.

Key Contributions:

• Created data governance frameworks ensuring privacy, security, and compliance with government regulations
• Developed comprehensive business cases resulting in $3.8M infrastructure cost reduction
• Mentored cross-functional teams on cloud-native data platform adoption and best practices
• Early adopter of AI-powered development tools (GitHub Copilot, GPT-4, Claude) to accelerate delivery

Technologies: Azure Data Platform, Databricks, Kubernetes, Python, Terraform, Power BI, Azure DevOps

Architected end-to-end data migration strategy from on-premises to cloud, establishing modern analytics capabilities and governance frameworks.

• Designed terabyte-scale cloud ERP data platform integrating ERP, CRM, and accounting systems into unified data mart
• Led executive workshops to align data strategy with business objectives and user needs
• Delivered $160K monthly savings through optimized cloud resource utilization
• Established metrics and KPIs for continuous improvement of data services

Technologies: Azure Synapse, Data Factory, Power BI, .NET, Blazor

• Designed and developed Java-based ETL applications processing large datasets from multiple sources
• Built RESTful web services using Spring MVC for secure data integration
• Created optimized SQL queries, stored procedures, and database objects improving data retrieval performance
• Implemented data validation frameworks to ensure accuracy and consistency across critical business datasets

Technologies: Azure Data Factory, Azure SQL, Power BI, Java, Spring MVC, C#, Python

• Designed and implemented cloud infrastructure solutions (AWS, Azure) supporting actuarial analytics platforms
• Automated infrastructure provisioning and deployment using CI/CD pipelines, reducing manual effort
• Optimized system performance and scalability for large-scale actuarial models
• Implemented cloud security best practices including identity management, encryption, and compliance monitoring

Technologies: Azure, AWS, Terraform, C++, C#/.NET, VBA/VB.NET

Skills Matrix:

Certifications:

• Art and Science of Machine LearningArt and Science of Machine Learning
  Coursera, Issued Sep 2018, Credential ID 2TCT6DGFGFN2

• Feature EngineeringFeature Engineering
  Coursera, Issued Aug 2018, Credential ID CGGX8B272VVJ

• How Google does Machine LearningHow Google does Machine Learning
  Coursera, Issued Aug 2018, Credential ID BQ69DRFAA9MM

Education:

• Bachelor’s degree in physics with Computer Science minor from the University of Waterloo, Canada. 2014.