Company preparationGuide 6 of 10
Google · Company guide · Guide 6 of 10
Google Data Engineering Interview Preparation
Prepare for Data Engineering interviews at Google using its published hiring-process and interview-tips pages, plus labelled practice questions on SQL, pipelines and large-scale design.
On this page
Verified and attributed information
Google publishes an official description of its hiring process, from application through interviews to a hiring decision.
Google publishes interview tips for candidates on its careers site, covering how to prepare to talk about yourself and the role.
Source: Google Careers: Interviewing at Google, best practices and tips
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, for each day, the number of users whose first-ever event happened that day.
Design a pipeline that processes billions of log events per day into hourly aggregates. How do you handle late events and reprocessing?
A daily table's row count dropped by 40% overnight. Walk through how you would investigate.
Explain how you would choose partitioning and clustering for a multi-petabyte event table queried mostly by date and user.
Tell me about a time you simplified a complex data system. What did you remove and why?
Preparation overview
Prepare in three areas: technical fundamentals, data system design, and behavioural stories. Read both official pages first: they describe the stages you will go through and how to prepare for interviews in general.
Technology focus
Expect SQL and coding fundamentals at scale: window functions, deduplication, aggregation, Python data processing and complexity analysis. Revise SQL fundamentals and the DSA pattern roadmap.
System-design focus
Practise designs where volume is the main constraint: log processing, partitioning and reprocessing. Start with the batch pipeline and clickstream case studies.
Behavioural preparation
Prepare specific stories with real details: a technical decision you made, a disagreement you resolved, a mistake you fixed, and impact you can describe honestly.
What this guide does not claim
This page does not state Google’s number of rounds, interview questions, levelling or pay. Where Google publishes information about its process, it is summarised above with a link; read the source for current details.