The workflow aims to help a Data Team Lead transform raw source table schemas and business requirements into well‑structured semantic models for dbt projects. It ensures that metrics have a single source of truth, models follow medallion or Kimball principles, and documentation and testing standards are consistently applied. The output includes a semantic model diagram, dbt project structure, metric definitions, and documentation guidelines.

The goal is to analyze cloud data warehouse usage and identify ways to reduce spend without compromising reliability or breaching contractual limits. The workflow must decompose cost drivers, propose safe optimization levers, and deliver a clear, ROI‑focused plan. Recommendations must include required approvals, rollback paths, and monitoring guardrails.

This workflow supports on-call data infrastructure leads in handling incidents from triage to postmortem. It provides structured steps to assess alerts, determine blast radius, communicate with stakeholders, form root-cause hypotheses, and produce a blameless postmortem with action items. The goal is to ensure fast, calm, and systematic incident resolution with clear accountability and prevention measures.