From Data Engineer to AI Architect — 90 Days

You're a good Data Engineer. You know Fabric, PySpark, Azure maybe DP-600 and DP-700 too. But you're still fixing the pipeline at 2AM, not in the room when the CFO decides the budget. The gap isn't more certifications. it's not knowing how to pitch, price, and package what you already know.

This is a 27-page working playbook built from real enterprise Fabric deployments — the exact prompts, pitch scripts, and pricing frameworks used to move from execution into architecture, pre-sales, and AI agent delivery. Every prompt is engineered against real constraints, not generic productivity fluff.

What's inside:

• 9 Master Prompts across Data Engineering, Pre-Sales, Agency Content, Quant Finance, and AI Agent Deployment
• The F-SKU Capacity & Cost Reference for defending Fabric decisions to a CFO
• The C-Suite Pitch Framework (Bleed / Blueprint / Yield) + 8 objection-handling scripts
• The 72-Hour RAG Agent Deployment Blueprint with a 4-tier SaaS pricing model
• A 6-table PostgreSQL portfolio schema + Python projection/stress-test functions
• 8 Bonus production-ready prompts (Delta Lake, ADF pipelines, DPDPA audits, and more)
• A 90-Day Action Plan from "read this" to "first paying client"

Not for: complete beginners with no Fabric/Azure/PySpark background, or anyone expecting a passive copy-paste prompt dump with no strategic context.

Built by a Fabric/Azure Data Engineer holding DP-600 and DP-700 certifications — this is the prompt library used in real production work, not a repackaged tutorial.