Your Ultimate Guide to the Google Data Engineer Interview Process

Focusing on the corporate philosophy of “work should be challenging and challenging should be fun,” Google predominantly ranks on Fortune magazine’s best companies to work for.

Therefore, landing a job as a data engineer at Google will open a range of opportunities for you. With excellent compensation, employee benefits, and innovative work culture, this FAANG company is one of the best places to work for data engineers. Needless to say, the Google data engineer interview process is pretty tough. But, it is certainly worth your efforts.

So, if you are preparing for a tech interview, check out our interview questions page and salary negotiation e-book to get interview-ready! Also, read Google Interview Questions and Google Coding Interview Questions for specific insights and guidance on Google tech interviews.

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In this blog, we’ll cover everything you need to know about the Google interview process for data engineers

  • Roles and Responsibilities of a Data Engineer at Google
  • What Is the Google Data Engineer Interview Process Like?
  • Google Data Engineer Interview Stages
  • How to Prepare for a Google Interview for Data Engineers? 
  • Google Data Engineer Interview Questions
  • Ace the Google Data Engineer Interview
  • FAQs on Google Data Engineering

Roles and Responsibilities of a Data Engineer at Google

If you are gunning for the data engineer job at Google, it is extremely important to understand what responsibilities you will be undertaking. Let’s take a look at them:

  • Develop, support, and design data warehouses, pipelines, and reporting systems. These are used to solve business operations, product, and user issues.
  • Make ETLs (export, transport, and load) and reporting systems for new data using large-scale and traditional data systems.
  • Influence users and product stakeholders and support engineers in ensuring the data infrastructure meets the evolving requirements.
  • Closely work with analysts to produce various mechanical and statistical learning modes using data processing pipelines.
  • Review and write technical documents. These include development, revision, and design documents.

What Does Google Look for in a Data Engineer?

Google follows a stringent process for hiring and operations. The company focuses on the following qualities in a data engineer job applicant:

  • Cognitive ability
  • Role-related knowledge
  • Leadership

What Is the Google Data Engineer Interview Process Like?

Google considers the hiring process as an important part of its culture. The company believes in building an inclusive workplace, beginning with the hiring process.

According to Google, it is difficult to build a career on something that fails to excite you. So, before you proceed to apply for a tech interview in Google, begin with asking these questions to yourself:

  • Are your past achievements a result of solo work or teamwork?
  • What do you enjoy more: solving problems or carrying the discussion forward?
  • What, according to you, was your most rewarding job? And why?
  • Describe to yourself the best team you have ever worked with. Also, formulate the reasons as to what makes the team stand out.

Google describes this exercise as the “self-realization” phase. It will help you in creating a clearer picture of what you want in life. Your skills, experiences, and goals are a part of your life, your triumphs, and your failure. Once you are done focusing on yourself, you can proceed forward with:

  • Your Resume: Build your resume by highlighting your skills and experiences that go with the job description. Also, mention if you have had any leadership roles in the past. Another important thing while building a resume is to keep it short yet informative.
  • Online Application: Use Google’s career search tools and apply for the job role of a data engineer.
  • Interviews: If the staffing members view your application as a right match, you will officially enter Google’s hiring process.

Recommended Reading: Data Engineer Interview Process

Google Data Engineer Interview Stages

This tech interview at Google primarily focuses on the following stages while hiring employees:

  • Online Assessments: After submitting your resume, you may be asked to take a brief online assessment.
  • Phone Screen: Before diving into more in-depth interviews, you will begin with a phone interview. Here, the interviewer will ask questions about your prior work experiences and your reason for working at Google.
  • Project Work: Next, you may be asked to complete project work. This could range from experimental designs to writing codes. This assessment helps the interviewer in understanding your way of approaching problems.
  • Onsite/In-depth Interviews: Google typically conducts 3-4 interviews. Each in-depth interview can last for 45 minutes with a team manager, hiring manager, and developer. These interviews cover a mix of both technical and behavioral questions.

Google Data Engineer Interview Timeline

You can expect the process to take anywhere from 2-6 months. Google puts a great deal of emphasis on hiring the ideal candidate for each job profile. Hence, make sure to draft the perfect resume and ace the interviews to land your dream job.

What Happens After The Interview – The Hiring Decision

After you are done with the interviews, the hiring team will bring everything together from your application and review it. The most stretched-out phase of the hiring process is the review stage. This can take several weeks and consists of the following two segments:

Feedback Stage

The interviewers submit their feedback in a standard format along with a numerical ranking. After that, HR conducts an automated search to find current Google employees who are alums of the same university or company as you. They then send an email to that employee to ask for their opinion of you.

Selection and Review

The hiring committee then prepares a candidate packet containing top picks and recommendations from the committee. Later, a senior Google executive will review the remaining applicants and decide on whom to hire. After this, the compensation committee determines the appropriate market compensation for the offer.

Once you make the cut, you will receive an offer with details about your salary and other perks. Reportedly, you will be given up to two weeks to decide whether to accept or reject the offer.

How to Prepare for a Google Interview for Data Engineers?

Interviewers at Google examine whether you are a perfect match for the job role or not by adhering to these:

  • Structured interviewing: Google will assess you using clear rubrics. These rubrics are used for every other candidate applying for the particular role. It is done to evaluate everyone from the same perspective.
  • Open-ended questions: Interviewers will ask you open-ended questions to learn how you solve problems. This will help them identify your strengths and how you interact with a team.

Thus, your prep should also be planned and structured to tackle any question you face during the interview.

To start, here are a few skills that you can brush up on while preparing for the Google data engineer interview:

Technical Skills:

  • SQL: This is a must-have skill if you are applying for a data engineer position at Google. All pipeline queries and exploratory data analyses are done in SQL.
  • Python: Most pipelines are written in Python. Besides the framework, it plays a part in statistical tests and data manipulation as well.
  • Unix: It is ideal to possess decent knowledge about Unix as most data engineers need to work on a dev server.

Other Skills:

  • Get into the Mind of the End-user: Here, “end-user” may mean the end-user of the product or the one at the end of your deliverable. Project empathy and intuition are some of the most crucial skills that a data engineer should possess.
  • Knowledge of Available Tools: Ideally, you must understand the trade-offs of various data engineering tools available to you.

Recommended Reading:
How to Prepare for Data Engineer Interviews
How to Prepare for Amazon Data Engineer Interview

Google Data Engineer Interview Questions

Google’s interview for data engineers includes multiple topics. After our rigorous analysis, we found the following topics that interviewers put more emphasis on while hiring candidates:

  • Python
  • SQL
  • Algorithms
  • Probability
  • Statistics or A/B learning
  • Machine learning
  • Product case, etc.

Here are a few technical questions that you can expect during your interview:

  1. Can you talk about the types of design schemas in data modeling?
  2. Explain the difference between structured and unstructured data.
  3. How would you proceed with developing an analytical product from scratch?
  4. Define Big Data and how is Hadoop related to it?
  5. What is a block, and what roles do block scanners play?

Recommended Reading:
Facebook Data Engineer Interview Questions
Uber Data Engineer Interview Questions

Ace the Google Data Engineer Interview

When it comes to interview prep, Interview Kickstart is the gold standard. We can help you cover all ground to ace the Google data engineer interview process. Here’s how you’ll benefit from our course:

  • Learn from 100+ interviewers, technical coaches, career coaches, and instructors from FAANG and other top Silicon Valley companies.
  • Learn “Power Patterns” — these will help you solve unseen coding problems during the interview process.
  • Get domain-specific training tailored for Data Engineers to crack every single interview round.
  • Practice mock interviews, get multiple feedback loops, and work on your interviewing skills with FAANG+ instructors.

Register for our FREE webinar now to uplevel your career!

FAQs on Google Data Engineering

1. Do Data Engineers at Google Write Code?

Yes, data engineers build infrastructure, tools, services, and frameworks and also write codes.

2. What Is the Difference Between a Data Analyst and Data Engineer?

Data analysts analyze numeric data and use it to help the company make better decisions. On the other hand, data engineers are involved in preparing the data.

Interview Process

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