# Three sources feed six custom point-to-point Python jobs that land directly into a finance dashboard Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem Three sources feed six custom point-to-point Python jobs that land directly into a finance dashboard, a product dashboard, and an ML feature store. There is no shared raw layer, no shared curated layer, custom-coded ingestion, one orchestrator owning everything, and no undercurrents. Apply the five redesign steps the section walks through to turn this into a layered architecture with named contracts, bought commodity tooling, and split DAGs at team boundaries. Postgres ingestion stays custom; only commodity SaaS connectors are bought. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/three-sources-feed-six-custom-point-to-point-python-jobs-tha-3a352745) - [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.