Enterprise AI, cloud & data

Skills

20 years of experience connecting product strategy, hands-on technical expertise, and enterprise delivery across financial services, AI, data, and cloud.

Product strategy & leadership

  • Customer discovery
  • Portfolio & roadmap strategy
  • 0-to-1 products
  • Product delivery
  • Adoption & go-to-market
  • OKRs
  • Change management
  • Startup advisory
  • Cross-functional leadership

In practiceLaunched 20+ data products and built and mentored a 50+ person product, engineering, data, and ML organization.

AI & machine learning

  • Generative AI
  • Agentic AI
  • Retrieval-augmented generation (RAG)
  • MCP & agent architecture prototyping
  • MLOps
  • Vertex AI
  • Python / PySpark
  • Natural language processing
  • Semantic intelligence

In practiceLaunched GenAI-assisted PySpark-to-BigQuery conversion that reduced migration effort by 60%. MCP work focused on architecture and proofs of concept.

Cloud & platform architecture

  • Google Cloud Platform (GCP)
  • Snowflake
  • BigQuery
  • Terraform
  • Vertex AI Workbench
  • API & service contracts
  • Distributed systems
  • Multi-tenant platforms
  • SaaS / IaaS / PaaS
  • UI & headless capabilities

In practiceOwned platform requirements for 10K+ users and 350+ applications, including API-driven provisioning, quotas, and workload isolation.

Data products & governance

  • Data governance
  • Data quality
  • Metadata enrichment & lineage
  • Master & reference data management
  • Data ingestion & curation
  • Data discovery
  • Data warehouses & data lakes
  • Stewardship workflows

In practiceCreated Calibrate, a self-service data quality product adopted by 3,500+ users and processing 600K+ checks daily.

Reliability & security

  • Non-functional requirements
  • SLOs & SLAs
  • Recovery & monitoring
  • Provisioning latency
  • Cost controls
  • RBAC & least privilege
  • Encryption
  • Data classification
  • Audit logging & governed access

In practiceSpecified reliability, isolation, auditability, and security requirements for a governed enterprise data and ML platform.

Product execution & collaboration

  • Product requirements (PRDs)
  • Acceptance criteria
  • Engineering roadmaps
  • Experimentation & feedback loops
  • Success measures
  • Lifecycle management
  • Backward compatibility
  • Stakeholder alignment
  • Team mentoring

In practiceLed 20 engineers and analysts to 100% on-time delivery for critical sourcing and distribution initiatives at Credit Suisse.

Certifications

  • Google Cloud Digital Leader
  • Certified Scrum Product Owner
  • Salesforce AI Associate