Google Data Engineer Interview Questions (2026)

Landing a Data Engineer role at Google requires targeted preparation. Google interviews typically consist of four to five rounds including phone screens, coding interviews, system design rounds, and behavioral interviews focused on Googleyness and leadership. Expect whiteboard-style coding problems, scalability questions, and scenarios testing your ability to work in ambiguous situations. This guide covers the most frequently asked questions and insider tips to help you succeed in your Google Data Engineer interview.

About the Google Interview Process

Google is known for its rigorous interview process that evaluates problem-solving ability, coding skills, and cultural fit through multiple rounds.

Google interviews typically consist of four to five rounds including phone screens, coding interviews, system design rounds, and behavioral interviews focused on Googleyness and leadership. Expect whiteboard-style coding problems, scalability questions, and scenarios testing your ability to work in ambiguous situations.

Why Google Data Engineer Interviews Are Different

Google Data Engineer interviews differ from standard Data Engineer interviews in several key ways. The company has a unique interview culture, specific evaluation criteria, and expects candidates to demonstrate alignment with their values and mission. Understanding these differences gives you a significant advantage over other candidates.

Top 10 Data Engineer Interview Questions at Google

1. A common Google interview question: Explain the difference between ETL and ELT.
2. A common Google interview question: How would you design a data pipeline for real-time analytics?
3. Google interviewers often ask: What is the difference between a data lake and a data warehouse?
4. A common Google interview question: Describe your experience with Apache Spark or similar frameworks.
5. A common Google interview question: How do you handle data quality and validation?
6. Google candidates should prepare for: What is data partitioning and why is it important?
7. Expect this at Google: How do you optimize query performance on large datasets?
8. At Google, you might be asked: Describe a complex data pipeline you have built.
9. Google interviewers often ask: How do you handle schema evolution in data pipelines?
10. A common Google interview question: What tools do you use for data orchestration?

Google-Specific Preparation Tips for Data Engineer Candidates

• Practice coding on a whiteboard or shared document without IDE assistance
• Study system design patterns for large-scale distributed systems
• Prepare examples demonstrating leadership without authority
• Focus on data structures and algorithms, especially graphs, trees, and dynamic programming
• Research Google's core values and prepare stories aligned with Googleyness criteria

General Data Engineer Interview Tips

• Be proficient in SQL and at least one programming language
• Understand distributed computing concepts
• Know common data modeling techniques
• Be ready to discuss data governance and compliance

Preparation Timeline for Google Data Engineer Interviews

• 4 weeks before: Research Google culture, recent news, and the specific team you are applying to.
• 2-3 weeks before: Practice technical questions daily and prepare behavioral stories using the STAR method.
• 1 week before: Do full mock interviews with HireFlow AI simulating Google interview style.
• Day before: Review your notes, prepare questions for the interviewer, and get a good night of rest.

Practice Google Data Engineer Interview with HireFlow AI — our AI adapts to Google's interview style and gives real-time feedback.