Hiring analytics engineers who will still be great in year two
A structured interview loop that filters for the traits that actually predict long-term impact.
SQL screens filter for competence at the median. They do not predict who will be great in year two.
The traits that do predict year-two greatness: comfort refactoring someone else's model, willingness to delete their own work, and the ability to describe a metric to a non-technical stakeholder without jargon.
None of those show up on a coding pad. So we test them explicitly, with a take-home refactor and a stakeholder-conversation roleplay. It takes more of everyone's time, and the hires are dramatically better.
Aisha specializes in semantic layers, dbt architecture, and getting analytics organizations to actually ship.
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