~$ whoami
A community about the problems in data engineering — not the tools. Ten years of building warehouses from scratch, and the lesson keeps repeating: the hard part is the data and the tradeoffs, not the tooling.
AI collapsed the cost of producing code. What's scarce now is the intuition to know what a system must do and what will quietly break — correctness first, scale second, and the judgment to direct AI well.
Spark, Flink, Debezium — tools get you 0 to 1; maintaining them is the headache. In the age of AI, judgment and a sacred problem statement are everything.
My first post. After years building big-data platforms from scratch, the hard part was never the volume — it's bad data, reliable sourcing, and asking the dumb questions first.