Dead Letter Queues

Concepts covered: paApiIngestion

What They Want to Hear 'A DLQ is where events go when they cannot be processed: malformed JSON, schema violations, unhandled exceptions. Instead of crashing the pipeline or silently dropping the event, I route it to a separate queue with the original payload plus the error metadata. Someone reviews the DLQ and either fixes the root cause or discards the events.'

About This Interactive Section

This section is part of the How Data Moves: Advanced 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.