PDF resource · ungated
Senior Engineer AI Architecture Checklist
An ungated one-page field guide for using approved AI to inventory duplicated semantic logic, organize human validation, and plan a governed gold-layer migration.
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Use case
The decision this resource helps clarify.
AI can accelerate implementation while also amplifying undocumented metrics, competing business definitions, and platform sprawl. The useful pattern is AI-assisted triage followed by accountable human decisions and governed architecture.
Built for: Senior data engineers, analytics engineers, architects, BI platform owners, and data leaders reviewing a fragmented Power BI, Fabric, or Databricks estate.
What is inside
- A six-step metadata-to-migration playbook
- Four exact prompts for duplication triage
- A validation-queue structure for domain owners and architects
- A gold-layer contract and incremental retirement path
How to use it
- Harvest and normalize metadata with approved enterprise tooling before asking AI to compare it.
- Treat AI output as a review queue, not as a system of record or an automatic consolidation decision.
- Validate business variations with accountable domain owners before migrating or retiring shared assets.
When the resource is not enough
Explore data architecture consulting
Use an independent architecture review when duplicated business logic, unclear ownership, or an ungoverned migration path creates material platform risk.