2.3. Implement Lifecycle Management

💡 First Principle: Production-grade data engineering requires the same discipline as software development: version control, automated deployment, and environment separation. Without these, you're one accidental change away from a production outage with no way to roll back. Think of lifecycle management as your "undo button" and "safety net" combined.

What breaks without proper lifecycle management? A data engineer makes changes to a lakehouse schema and pipeline. Without version control, reverting a bad change requires manual reconstruction from memory. Without deployment pipelines, promoting to production means copying and pasting configurations—and hoping you didn't miss anything. Every manual step is an opportunity for human error.