Independent audit of an enterprise Databricks Lakehouse
Led a 10-day independent audit of a global mining company's enterprise Databricks Lakehouse platform across three pillars (Ingestion, Data Governance, Technical Governance), delivering evidence-backed findings from production environment analysis of 16,000+ tables across two AWS regions and three stakeholder workshops.
Role: Lead Auditor / Principal Consultant
- tables analysed across two AWS regions
- 16,000+
- tables analysed across two AWS regions
- remediation roadmap delivered
- 21-point
- remediation roadmap delivered
- from kickoff to Conditional Go
- 10 days
- from kickoff to Conditional Go
The approach
Led a 10-day independent audit of a global mining company's enterprise Databricks Lakehouse platform across three pillars (Ingestion, Data Governance, Technical Governance), delivering evidence-backed findings from production environment analysis of 16,000+ tables across two AWS regions and three stakeholder workshops. Identified critical gaps including zero governance tagging, absent architectural target state, and stalled data transformation pipelines, corroborated by four independent sources. Delivered a Conditional Go assessment with a 21-point remediation roadmap, 7 conditional actions with defined timeframes, and a consolidated risk register accepted by client, vendor, and consulting leadership.
Related projects
- Aware SuperSuperannuation2026
AI response evaluation framework for multi-agent RAG
Designed an evaluation framework to systematically measure the accuracy, relevance, groundedness, and safety of AI responses generated by Aware Super's multi-agent RAG system over Azure AI Search, benchmarked against a curated golden dataset.
- quality gates evaluated: routing, retrieval, response
- 3
- quality gates evaluated: routing, retrieval, response
Azure FoundryMicrosoft Agentic FrameworkMicrosoft Evaluation - NSW Government (DCCEEW)Government2026
Secure, governed Google Cloud AI sandbox
Built a governed, security-hardened Google Cloud environment for AI/Vertex AI PoCs, fully as Terraform IaC — Shared VPC with default-deny egress + per-PoC isolation, least-privilege IAM (service-account impersonation), org-policy guardrails, IAP bastion, audit logging and cost budgets, with a reusable project factory to onboard new teams in minutes under security guardrails by default.
- to onboard a new team, guardrails by default
- Minutes
- to onboard a new team, guardrails by default
TerraformGCP Vertex AIGCP Shared VPCGCP Cloud NATGCP IAM - ChevronEnergy2025
Global data model products for the Advanced Analytics Platform
Data model products were developed for Chevron’s Data Analytics Platform to support Mobile Inspections, Engineering Documents, and Equipment management.
AzureDatabricksErwinInformaticaADF