# A regional bank closes the books at midnight and needs the leadership meeting at 8am to read the day Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem A regional bank closes the books at midnight and needs the leadership meeting at 8am to read the day's transactions on a dashboard. The canvas already has the endpoints of the nightly batch shape: a MySQL transactions source on the left and a Looker executive dashboard on the right. Apply the canonical nightly-batch run this section just walked through and add the missing middle: a raw-zone storage node (S3, GCS, or ADLS) where the nightly extract lands as a partitioned file, a curated transform (dbt is the standard) that reads raw and writes the daily_balances table, a warehouse (Snowflake, BigQuery, Redshift, or Databricks) that holds the curated table, and an orchestrator (Airflow, Dagster, or Prefect) that wakes the job once a day at 2am Pacific. Tag the curated warehouse table with a daily slaFreshness (< 24h) so the contract to the morning consumer is named. The pipeline runs once per day; nothing on this canvas runs continuously. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/a-regional-bank-closes-the-books-at-midnight-and-needs-the-l-c5621942) - [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.