Backfills as First-Class Operations

Concepts covered: paBackfill, paIdempotentBackfillRequirement

A backfill is the operation of running a pipeline over a historical date range that it did not run for at the time. Backfills happen for three reasons: a bug in the pipeline produced wrong data and the corrected pipeline must reprocess the affected dates; a new column was added and the historical data must be regenerated to fill it; a new pipeline is launched and needs initial history. In production, backfills are run constantly, and a system that does not treat them as a first-class operation produces a different bug every time. What Makes Backfills Different From Regular Runs A regular run processes one logical date: today, or the most recent hour. A backfill processes many logical dates, sometimes years of them. The same task is invoked once per logical date, with different parameters,

About This Interactive Section

This section is part of the Orchestration and Dependencies: 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.