Subjects

SQL Mental Model & Query Execution Order

The foundational SQL subject every data engineering interview loop assumes you already have: the logical order the database actually evaluates a query in (FROM/JOIN, WHERE, GROUP BY, HAVING, SELECT, DISTINCT, ORDER BY, LIMIT) versus the order you type it in, why that gap explains half of the 'why doesn't this query work' confusions candidates hit, JOIN types reasoned about by row count rather than memorized as Venn diagrams, UNION/INTERSECT/EXCEPT set semantics, the three-valued logic that makes NULL comparisons and the NOT IN trap so dangerous, GROUP BY/HAVING as a mental model rather than a syntax rule, and a fully worked step-by-step trace of a non-trivial query.

dbt & Analytics Engineering

A practitioner's tour of dbt and the analytics engineering discipline it created: what analytics engineering is and why it sits between data engineering and analysts, how ref() and source() build a dependency DAG out of plain SQL, the four materializations and when each one earns its cost, incremental model strategies (merge vs insert_overwrite, unique_key, is_incremental()) with a worked example, the testing and documentation layers that make a warehouse trustworthy, and the staging/intermediate/marts project structure nearly every serious dbt project converges on.