Google Data Engineer Interview Guide
Detailed, specific guidance on the Google Data Engineer interview process - with a breakdown of different stages and interview questions asked at each stage
The role of a Google Data Engineer
Data engineering is currently one of the fastest-growing roles, and it is no surprise that Google considers it a super important one within its organizational framework. Data engineers must have an in-depth understanding of data trends as well as various technologies associated with them. Data engineers face the challenge of building reliable and scalable solutions, which will work within the size and scope of the company.
A professional Data Engineer has to collect, transform and publish data and make decisions revolving around data. At Google, you will be part of teams that implement vendor-sourced enterprise software, configure the software, customize it, and integrate it. Google expects its data engineers to translate the needs of the consumer into technical specifications, and advocate them to research scientists, engineering teams, and business audiences. For more insights, explore the Google Data Scientist and Microsoft Data Engineer guides.
Data engineers at Google must be able to:
- Deal well with an ambiguous environment with often vague requirements, prioritize work for themselves, and deliver results in a fast-paced, rapidly changing environment.
- Battle large system processes with expertise and integrate their work with other internal systems. This is similar to the challenges faced in large-scale data systems, which are also covered extensively in the Apple Data Engineer guide.
- Communicate well to maximize collaboration with analysts and business process owners, and meet the needs of the customer effectively.
- They must have a good understanding of Big Data and Google Cloud Platform technologies so that they can fulfill the needs of the customer in the most efficient way.
Google Data Engineer Interview Guide
The Google Data Engineering interview has 3 rounds:
The first is an online coding test, based majorly on SQL and Python. The next round is a Technical Phone Interview which focuses on database management, big data, and algorithms. The final round is the Technical round, which has 3 interviews covering SQL, Shell scripting, and Business Analysis.
Relevant Guides
Google Data Engineer - Online Coding Test
Overview
The coding test is used to screen candidates of certain specific career levels and in some geographies. It may not be offered to all candidates (last reported by a candidate in 2018).
What the interviewer will assess
Technical questions will be asked related to -
- SQL
- Python
You can expect both multiple-choice type and long answer type questions.
Google Data Engineer - Technical Phone Screening
Overview
This is a technical phone screening round.
What the interviewer will assess
The interviewer will assess your database management skills and knowledge of big data and algorithms. The interviewer may also discuss your role and experiences. Your speed and efficiency in solving coding problems will be tested.
Tips
- Have a thorough understanding of Database Management and how you will work with a huge amount of records.
- Prepare well for questions on big data technology.
- Have a good command of data structures and algorithms.
- Keep answers short and crisp.
- Highlight the relevant and most recent experiences which accentuate your skills related to data engineering.
Interview Questions
- How can strings be divided (using Python or any other language)? How can it be scaled into a large number of records?
- Design a relational database system for a specific business case.
- Questions based on experiences -
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Google Data Engineer - Technical Round
Overview
In this interview, you’ll be talking to several people, including possibly a future team member, most likely a Data Engineer at Google. The interview typically takes 45-60 minutes. Much time will not be spent on introductions and you can expect the interviewer to jump directly to the technical questions. The questions will revolve around -
- SQL
- Shell scripting
- Business Analysis
You might also find the Spotify Machine Learning Engineer guide useful.
What the interviewer will assess
- Your understanding and command of SQL. For example, in Facebook's data analyst interview, you might be asked to demonstrate your SQL skills through practical problems involving joins, subqueries, aggregations, filters, and case statements.
- Your mastery of shell scripting, how well you can execute a given task with the minimum number of commands, and how much clarity you have for the commands.
Tips
- Explain each step to the interviewer so that they know how you are tackling the problem. They may occasionally intervene and clarify the procedure, or question you on how an alternative way would work. They may also drop in a hint or two, and we’d always recommend watching out for these and adapting your answer to incorporate them.
- Have a good command of joins, subqueries, aggregations, filters, case statements. The more you practice, the more confident you will be during the interview.
- Be prepared for general programming questions to be attempted in a language of your choice. This reduces the odds of you encountering a new syntax you haven’t faced before. As a Data Engineer at Amazon, being versatile in programming languages and familiar with various technologies will be beneficial, especially when discussing your technical expertise during interviews.
Interview Questions
- How can you obtain the top ten values (from a given column) from a comma-separated file?
- How to sum all values in a range of values between A and B.