Build the platform or use the platform: the two Databricks data engineer tracks nobody names

Two Databricks engineers sit at adjacent desks. Same title, same pay, same words in the ladder document. Watch a year go by, and they are not doing the same job.

Both get rated strong. Both get told they're ready for more scope. Nobody says the useful thing: the evidence those two are stacking isn't interchangeable, and one of those years makes no sense on the other one's promotion packet.

In this episode:

- Why the data engineering ladder quietly forks, and why that fork is missing from every ladder document

- The five-minute question that tells you which track your last year of Databricks work actually built toward

- How each track reaches staff, and the very different proof each demands

- Where each track stalls a good year, and what to say in your next one on one to get moved off it

This episode is for Databricks data engineers past the junior stage who keep getting strong reviews and vague answers about what's next. Whether you write the cluster policies and ingestion frameworks or ship the tables the business argues from, you'll walk away able to name your track and ask for the work that gets you to the next rung.

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Helping 18,000+ Databricks data engineers become seniors: interview like seniors, execute like seniors, think like seniors.

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