Schema Migration

Concepts covered: paSchemaEvolution

What They Want to Hear 'I enforce backwards compatibility by default. New columns are added with a default value. Old columns are never removed in the same release as the new ones: I deprecate first, migrate consumers, then remove. For breaking changes, I version the schema and run both versions in parallel during the migration window.' This is the answer that shows you think about consumers, not just your own pipeline.

About This Interactive Section

This section is part of the Keeping Data Fresh: Intermediate lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

How DataDriven Lessons Work

DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.