data-engineering

How Apache Spark works: RDDs, lazy DAG execution, drivers and executors, Spark SQL, AQE, streaming, and when single-node tools like DuckDB or Polars fit better.

Data engineering vs data science: what each role does, the skills and tools they need, how the work differs, and how to choose or switch between them.

Iceberg vs Delta Lake vs Hudi in 2026: how each lakehouse table format works, where each wins, how catalogs and migration fit, and how to choose.

Data contracts explained: what they contain, how dbt model contracts and Schema Registry enforce them, where they fail, and a rollout plan for small teams.

dbt (data build tool) explained for data analysts: SQL-based transformations, models, tests, documentation. The modern way to build data pipelines.