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What Are the Roles and Responsibilities of a Google Data Engineer?

Posted on 
August 12, 2021
|
by 
Team Interview Kickstart

With time, companies are becoming more reliant on data. It’s only natural that the demand for data engineers is also increasing by the day, and so is the fierce competition. In this regard, Google is one the best companies to work for data engineers. The company offers exceptional career opportunities, salaries, and a range of employee benefits. That said, it is pretty difficult to land a job at this renowned FAANG company. However, with the right qualifications, experience, and hard work, it is not impossible.

If you are preparing for a tech interview, check out our interview questions page and salary negotiation ebook to get interview-ready! Also, read Google Leadership Principles Interview Questions and Google Coding Interview Questions for specific insights and guidance to uplevel your Google tech interview prep.

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In this article, we will focus on the roles and responsibilities of a Google data engineer, which will help you understand the role position better, which will in turn aid your interview prep. Here’s what we’ll cover:

  • What Does a Google Data Engineer Do?
  • Top Skills Required to Be a Google Data Engineer
  • Google Data Engineer Roles and Responsibilities
  • Tips to Prepare for Your Google Data Engineer Interview
  • FAQs on Data Engineering at Google

What Does a Google Data Engineer Do?

Data engineering is the process of transforming raw data to a usable format, which is then further analyzed by other teams. Cleansing, organizing, and manipulating data using pipelines are some of the key responsibilities of a data engineer at Google.

You will also work on applying data engineering principles on the Google Cloud Platform to optimize its services. As a Google data engineer, you will also have to collaborate with engineers, marketing teams, product managers, sales associates, etc. These collaborations will help you to identify customer behavior and enhance network structure optimization accordingly.

Top Skills Required to Be a Google Data Engineer

If you’re looking to become a Google data engineer, you must possess the following skills to be eligible:

Technical skills:

  1. A solid grip over programming languages, like Python, Scala, C++, etc.
  2. In-depth knowledge about SQL databases and ability to execute queries quickly. 
  3. Knowledge of data warehousing and data modeling.
  4. Understanding of UNIX and GNU/Linux systems.
  5. Knowledge of how to maintain ETLs operating on a variety of structured and unstructured sources.
  6. Fundamentals of Kafka to handle real-time data feeds.
  7. Understanding of how to use Kafka with Hadoop.
  8. Knowledge of data structures and algorithms. 

Soft skills:

You also need to possess exceptional communication and comprehensive abilities. Furthermore, your analytical skills are also paramount for this job. Some of the key soft skills required are:

  1. Punctuality
  2. Adaptability
  3. Critical thinking ability
  4. Ability to work solo and as a part of a team
  5. Social skills
  6. Innovation
  7. Proactiveness
  8. Decision-making
  9. Observational skills

Google Data Engineer Roles and Responsibilities

Some of the most important roles and responsibilities of a Google data engineer include:

  • Working with large datasets and solving difficult analytical problems is a primary task of a Google data engineer.
  • Conducting end-to-end analyses, including data collection, processing, and analysis.
  • Building prototype analysis pipelines to generate insights. 
  • Developing comprehensive abilities for Google data structures and matrix for upcoming product development and sales activities is also a crucial task for Google data engineers.
  • Finding trends in data sets and developing an algorithm to make raw data more useful across teams.
  • Designing, building, operationalizing, securing, and monitoring data processing systems on Google Cloud Platform.
  • Deploying, leveraging, and continually training and improving existing machine learning models.
  • Identifying, designing, and implementing internal process movements 
  • Automating manual processes to enhance delivery. 
  • Meeting business objectives in collaboration with data scientist teams and key stakeholders.
  • Creating reliable pipelines after combining data sources.
  • Designing data stores and distributed systems. 

Tips to Prepare for Your Google Data Engineer Interview

Now that you’re aware of what your job as a data engineer at Google entails, here are some tips to help get your interview prep started:

  1. Coding Challenges With HackerRank or LeetCode: During the phone screen or on-site interviews, chances are you will require solving some coding problems within specific time limits. Practicing with LeetCode or HackerRank will, thus, help to boost your speed.
  2. Whiteboard Practice: If you practice answering technical interview questions using a whiteboard, it can help you immensely in specific rounds.
  3. Brush Up Your Soft Skills: Data engineers often need to collaborate with multiple teams to collect necessary data and analyze them subsequently. This requires observational and team communication skills of the highest order. Developing and maintaining a friendly and helpful personality can do wonders during a Google data engineer interview.
  4. STAR Method for Behavioral Questions: Using the STAR method (Situation – Task – Action – Result) is a suitable way to answer behavioral questions. Hence, note specific situations which exhibit specific qualities and indicate your approach to solve a problem.
  5. Review Literature and Best Guides: You can also uplevel your knowledge from documents by widely used frameworks or tools. These include Google Python Style Guide, Oracle Database SQL Tuning Guide, or GitHub Best Practices, among others.

For more information about the data engineer interview process, read:
Data Engineer Interview Process
How to Prepare for Data Engineer Interviews

5 Most Common Questions Asked During a Google Data Engineer Interview

  1. What is your experience in data modeling? What modeling tools do you use?
  2. How would you design a relational database system for a specific business case?
  3. Write SQL with join, sum, and count.
  4. What is your approach to building an analytical product from ground zero?
  5. Explain Heartbeat in Hadoop.

Check out the following articles for more interview questions:
Facebook Data Engineer Interview Questions
Uber Data Engineer Interview Questions

Start Your Data Engineer Interview Prep Today!

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Our curriculum is one-of-its-kind and tailored to data engineers to help you crack the toughest tech interviews at FAANG+ companies. You’ll learn from instructors who are an integral part of the interview machinery at top tech companies. With detailed guidance from experienced instructors and interview coaches, you will be a step closer to grabbing your dream data engineer role. 

Want to know more? Register for our free webinar and uplevel your career. 

FAQs on Data Engineering at Google

1. What is the average salary of Google Data Engineers?

The average salary of experienced data engineers at Google varies between $150,000 and $350,000. However, this also comes with a range of best-in-class benefits like health insurance, flexible work schedule, and hybrid work culture.

2. How Does Google Provide Work-life Balance to its Data Engineers?

For data engineers, Google allows flexible working hours, along with options to work from home, take leaves for family emergencies, or a PTO of 15 days for the first 3 years, 20 for fourth and fifth years, and 25 a year after that.


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