# A backend team shipped a new field on the checkout_completed event Tuesday afternoon: discount_code_ Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem A backend team shipped a new field on the checkout_completed event Tuesday afternoon: discount_code_applied. The pipeline's loader has been writing to a strict-schema target table for six months and started failing the moment the new field appeared. The section names three reactions a loader can have to an unexpected field (reject, silent drop, accept), and the canonical fix is to land the raw payload in a flexible format so the new shape does not crash the pipeline. Spot the broken loader on the canvas: replace the strict-schema warehouse loader and target with a destination that accepts the variant payload (a JSON or VARIANT column in Snowflake or BigQuery, an Avro-tagged record on a topic backed by a schema registry, or a lakehouse table format whose schema_evolution lets new columns appear without a rewrite). The downstream dashboard must read from the new destination. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/a-backend-team-shipped-a-new-field-on-the-checkoutcompleted-6b3bfdb8) - [System Design Interview Questions](https://datadriven.io/data-engineering-system-design) - [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep) - [Daily Challenge](https://datadriven.io/daily) --- Source: DataDriven (https://datadriven.io). 100% free data engineering interview prep. Live code execution against Postgres 16, Python 3.11, and Spark sandboxes. No paywall, no premium tier, no signup gate.