Uday Kakkar

Senior Cloud & Data Architect with 18+ years of progressive experience designing and implementing enterprise-scale cloud transformations, AI/ML platforms, and data governance solutions across GCP, AWS, and Azure. Proven track record delivering complex multi-cloud and generative AI solutions for law enforcement, federal government, financial services, and telecommunications sectors. Masters in Electrical and Computer Engineering from UBC Vancouver.

Director & Principal Cloud Architect at KUBESHOT CONSULTING INC (2020-03 – Present)

Founded and lead boutique cloud consulting practice specializing in enterprise cloud transformations, AI/ML platforms, and data governance solutions. Deliver end-to-end solutions from strategy and architecture through implementation and operations for law enforcement, government, and Fortune 500 clients.

• Established multi-cloud and AI/ML managed service offerings generating $5M+ annual revenue
• Built high-performing team of cloud and AI/ML engineers, growing from solo practice to 5 consultants
• Defined service delivery methodologies aligned with PMBOK and cloud adoption frameworks
• Negotiated and managed contracts with government agencies, law enforcement, and enterprise clients

GCP Lead & AI/ML Architect at Ottawa Police Service (2024-04 – Present)

Leading comprehensive GCP-based AI/ML and data platform transformation for Ottawa Police Service, encompassing enterprise data strategy, generative AI implementations, and large-scale data migration from legacy systems.

• Architected and implemented enterprise AI strategy leveraging GCP Vertex AI, Gemini, and Document AI for law enforcement operations
• Built production-grade BigQuery MCP (Model Context Protocol) server using Claude Anthropic API enabling natural language interaction with law enforcement data
• Designed and deployed Document AI search engine using Vertex AI Search and Gemini for intelligent document discovery and analysis
• Implemented MLOps pipelines for model training, deployment, and monitoring using Vertex AI pipelines
• Developed generative AI applications for operational intelligence, case analysis, and predictive analytics
• Built comprehensive Data Governance Portal managing 121 datasets, 916 tables across 30 data groups
• Designed multi-domain data architecture covering Operations, Workforce, and Financial analytics with 1.56 billion total rows
• Implemented staged data pipeline architecture: Raw → Staging → Curated → Analytical layers with 16 production-enabled projects
• Established data lineage tracking, metadata management, and data quality frameworks using Dataplex
• Created dual-environment strategy (Production/Non-Production) with proper separation and access controls
• Led full-scale Cloudera to BigQuery data migration including data lake, Hive metastore, and analytics workloads
• Architected BigQuery data warehouse with optimized table design, partitioning, and clustering for law enforcement queries
• Implemented Dataflow pipelines for real-time and batch data processing from operational systems
• Designed secure data ingestion patterns complying with law enforcement data protection requirements
• Established consistent naming conventions across all projects (e.g., prj-opol-*) for organizational clarity
• Implemented VPC Service Controls and security architecture meeting law enforcement data protection standards
• Designed IAM policies and access controls for sensitive law enforcement data with audit logging
• Established data classification framework and PII protection mechanisms using DLP API
• Implemented encryption at rest and in transit for all data assets with key management via Cloud KMS
• Delivered 858 tables and 228 analytical views supporting operational decision-making
• Enabled natural language querying of law enforcement data reducing analyst query time by 75%
• Achieved architectural maturity with clear separation, consistent naming, and staged data pipelines
• Reduced data platform operational costs by 40% through Cloudera to BigQuery migration
• Established foundation for predictive policing and operational intelligence using AI/ML

Cloud Practice Lead at Intuitive Cloud Partners (2023-04 – 2025-10)

Lead practice development for GCP professional services including migration, modernization, and managed services.

• Define technical standards and best practices for cloud-native application development
• Conduct architecture reviews and technical governance for 15+ concurrent client engagements
• Provide pre-sales technical consultation and solution design for deals valued at $500K-$3M
• Designed and delivered full-scale GCP Landing Zone with enterprise security controls
• Implemented Binary Authorization and SLSA v3 compliance for serverless deployments (Cloud Run, Cloud Functions)
• Architected secure CI/CD infrastructure using GitLab with automated security scanning and policy enforcement
• Led GitLab-to-GitHub migration for 200+ repositories with zero downtime
• Developed Python frameworks for automated GCP project provisioning and repository onboarding

Senior Technology Consultant at Bank of Montreal (BMO) (2022-05 – 2023-06)

• Delivered enterprise-grade AWS App Mesh service mesh architecture for microservices communication
• Implemented security controls meeting banking regulatory requirements (OSFI, PCI-DSS)
• Designed and implemented CI/CD pipelines for serverless applications using AWS CDK
• Developed Level 1, 2, and 3 CDK constructs in Python for standardized deployments
• Reduced infrastructure costs by 35% through serverless adoption and right-sizing initiatives

Cloud Consultant at MTS Solutions (2022-02 – 2022-07)

• Architected hybrid cloud solutions integrating Azure, AWS, and on-premises infrastructure
• Implemented Kubernetes-based microservices platform serving 100K+ daily active users
• Designed disaster recovery solutions with RPO<15min and RTO<1hr

Senior Architect at TELUS Communications (2021-05 – 2022-03)

• Led cloud migration of video services infrastructure serving 2M+ subscribers
• Orchestrated migration of petabyte-scale telecommunications data to GCP
• Architected topology for 50+ microservices deployed on Azure and AWS
• Achieved 40% cost reduction while improving service reliability to 99.95% uptime

Masters in Electrical and Computer Engineering – UBC Vancouver