Company preparationGuide 2 of 10
Amazon · Company guide · Guide 2 of 10
Amazon Data Engineering Interview Preparation
Prepare for Data Engineering interviews at Amazon using its published Leadership Principles plus clearly labelled practice questions for SQL, modelling and design.
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Verified and attributed information
Amazon publishes a set of Leadership Principles that describe how it expects employees to work, which makes them a sensible basis for preparing behavioural answers.
Source: Amazon: Leadership Principles
Sources
Reported candidate questions
None yet. A question appears here only with a named, attributable source.
Representative practice questions
These are practice questions written for this guide. They are not claimed to be questions this company has asked.
Write a SQL query that returns each customer's most recent order, including customers who have never ordered.
Design a star schema for an online store's order process. What is the grain of your fact table?
A daily pipeline was rerun and revenue doubled for one day. How would you find the cause and prevent it?
Design a pipeline that ingests clickstream events and produces hourly metrics. How do you handle late events?
Tell me about a time you found a data-quality problem nobody had asked you to look for. What did you do?
Preparation overview
Prepare in three areas: technical fundamentals (SQL, data modelling, pipelines), design (batch and streaming data systems), and behavioural stories. Because the behavioural framework is published, you can prepare for it far more precisely than for technical rounds.
Technology focus
Data Engineering roles generally test SQL fluency, data modelling and pipeline reliability. Strengthen these first:
System-design focus
Practise talking through a full design: requirements, scale, storage, processing, orchestration, reliability, data quality and cost. Start with the scalable batch pipeline case study.
Behavioural preparation
Read the published Leadership Principles and prepare two or three specific stories for each that you could tell in a structured way (situation, task, action, result). Use real situations and real results. Interviewers probe details, so invented or exaggerated stories fall apart quickly.
What this guide does not claim
This page does not describe Amazon’s interview loop, number of rounds, bar-raiser process or any specific question, because we have not yet verified those with attributable sources. When we can cite them, they will appear above with the appropriate label.