You are meeting a manufacturing customer evaluating Databricks for predictive maintenance across 40 factories. Their sensors generate 1.2 million events per second, they need anomaly alerts within 5 minutes, daily retraining on 15 TB of new data, and dashboard freshness under 10 minutes, while keeping annual infrastructure spend below $2.5M. In the interview, role-play how you would first align with the VP of Operations on business outcomes and ROI, then explain the proposed Databricks architecture to both the executive and the lead data engineer, translating technical choices like Delta Live Tables, Structured Streaming, MLflow, and Unity Catalog into business terms. The candidate should be pushed to justify sizing assumptions, discuss ingestion and storage capacity planning, and explain what compromises they would make if the customer insists on lowering cost by 30% without missing the alerting SLO.