Positioning
Data that holds up decisions, not just decks
I design and deliver analytics end to end on Microsoft patterns: ingestion, layers, modeling, governance and consumption. What I care about is after go-live: capacity, reconciliation and who operates it.
Journey
I started in infrastructure and support, moved through performance and BI, led data projects and landed in Analytics Engineering with Fabric, lakehouse and business in the same package.
Today I’m often between capacity incidents, sensitive-history migrations and metric definitions with finance or HR. Pipelines and models are the means; trustworthy decisions are the end.
How I approach projects
- Question before tool: without a decision to serve, engineering is fixed cost.
- Layers with contracts: bronze lands, silver standardizes, gold answers the business. Otherwise reconciliation never ends.
- Operations and owners: RLS, workspace, docs and usage rituals. Otherwise the report is decoration.