Most interview prep teaches you what to know. Not how to think. That's a problem, because data engineering interviews don't fail candidates on knowledge gaps as often as people assume. They fail candidates who know the answer but can't show their work. I watched "Data & AI Guy" solve five real interview questions live on camera using DataDriven.io. SQL, Python, Spark, data modeling, pipeline architecture. One problem per domain, full reasoning narrated out loud. It's a useful model for how to actually behave during an interview. Not just what to code, but how to move through the problem from prompt to solution to edge cases. SQL : Say the Why Out Loud The problem: return a deduplicated list of regions from an infrastructure nodes table. Answer is SELECT DISTINCT region FROM infra_nodes. One line. Correct. Most people write it and wait. He writes it and immediately explains why DISTINCT over GROUP BY. Both work here. But DISTINCT signals intent. You're not aggregating, you're deduplicating.…