About

I help enterprises design and deliver governed AI and modern data platforms—secure, audit-ready, and scalable across cloud and hybrid environments.

My work sits at the intersection of executive strategy and production delivery: establishing the architecture, governance, and operating model required to deploy AI safely in regulated environments. I’ve led architecture and delivery across Google, Microsoft, and Cloudera—helping organizations modernize data foundations, adopt cloud-native patterns, and operationalize AI with evaluation, observability, and security guardrails.

Google (San Francisco) · Microsoft (Seattle) · Cloudera (Toronto)

Highlights

  • •18+ years across Google, Microsoft, and Cloudera delivering production-grade AI/ML and modern data platforms.
  • •Builds and scales distributed teams; strong executive communication and cross-functional alignment.
  • •Deep focus on governance: residency, access controls, auditability, evaluation/observability, and Responsible AI.
  • •Published: “Architecting Sovereign AI: Implementation Strategies for Snowflake and Databricks.”

Certifications

  • •Google Professional Data Engineer
  • •Microsoft Certified: Azure Data Scientist, AI Engineer, Data Engineer
  • •Databricks Generative AI Fundamentals
  • •AI Product Management (Udacity)
  • •MIT: Tackling Challenges of Big Data