Big data is growing at an ever-increasing rate, and everything around us is data-driven. So it’s hardly surprising to know that among the numerous tech jobs, data engineering was ranked as the fastest-growing career option in 2020 (Dice 2020 Tech Job Report).
FAANG and several other companies across industries are constantly in need of qualified data engineers who can create systems that collect, manage, and convert the data into useful information for analysts.
If you aspire to have a career in data engineering and wonder how to prepare for a data engineer interview, you have come to the right place. At Interview Kickstart, we believe that with the correct preparation strategy, you can crack these interviews and land a data engineer job at leading tech companies.
Having trained over 6,000 software engineers, we know what it takes to crack the toughest tech interviews. Since 2014, Interview Kickstart alums have been landing lucrative offers from FAANG and Tier-1 tech companies, with an average salary hike of 49%. The highest ever offer received by an IK alum is a whopping $933,000!
At IK, you get the unique opportunity to learn from expert instructors who are hiring managers and tech leads at Google, Facebook, Apple, and other top Silicon Valley tech companies. That’s not all! We offer domain-specific interview prep programs, which includes a tailor-made Masterclass for Data Engineers.
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We have put together the ultimate guide on the data engineer interview process to maximize your chances of success.
Here’s what we will cover in the article:
- What does a data engineer do?
- What is the difference between a data engineer and a data architect?
- How to become a data engineer
- Data engineering job prospects
- What’s the interview structure like for data engineers?
- Interview study guide for data engineers
- Tips to crack your data engineering interview
- Examples of data engineer interview questions
- Data engineering career FAQs
What Does a Data Engineer Do?
In simple words, the primary job of a data engineer is to source and collect data from a variety of sources and make it easy to comprehend so that businesses can use that for improving their performance and growth.
As a data engineer, your responsibilities will include setting up and maintaining data infrastructures to support information systems and processes of businesses. These systems serve as the backbone of machine learning and AI analytics that can be used for processing a large variety of information and help in other essential activities such as data modeling, data transformation, and acquisition.
What Is the Difference Between a Data Engineer and a Data Architect?
Software engineers often tend to get confused between the data engineer and a data architect roles and end up using these terms interchangeably. Though these roles sound similar, the job descriptions are poles apart.
The universe of data engineering has several players, and data engineer is one of them. Another critical role is performed by a data architect responsible for designing the data management systems for integrating and managing various sources of data used by the engineers.
In other words, while data architects visualize the data framework, data engineers are responsible for creating such a framework.
How to Become a Data Engineer and Where You Can Work
You can explore various paths to become a data engineer once you have obtained your bachelor’s degree in engineering, computer science, physics, or applied mathematics. These include:
- Obtaining professional certifications from tech companies such as Google, IBM, Oracle, Microsoft, etc.
- Enrolling for online courses to brush up your skills in coding languages, operating systems, and machine learning
- Learning through projects that you can undertake on GitHub and writing extensively about your research on topics related to data engineering. Having a repertoire of published articles and a portfolio of projects can go a long way in establishing your credential as a data engineer before any prospective employer.
If you are serious about cracking data engineer interview questions, here are some technical skills you need to brush up on:
- Your programming skills need to be top-notch as the entire universe of data engineering focuses heavily on Python and Scala. Make sure to learn the coding best practices so that you can write efficient codes and create software. Knowing essential programs such as Apache Hadoop and C++ can be helpful.
- Learning automation and scripting is important as working with big data is tedious. Several data engineers consider shell scripting to be helpful in running various programs.
- Data warehousing is essential for storing a massive volume of data. That’s why you are expected to be familiar with cloud services platforms such as Google Cloud or AWS to use the data storage tools.
- Data engineers also need to know the basics of machine learning to help them develop efficient data pipelines.
- Since APIs are an integral part of data processing, which allows scientists and analysts to request relevant data, working knowledge of how the interface works is a valuable skill to have.
- Soft skills such as strong interpersonal communication, presentation, and teamwork are also good to have if you are considering a career in the field of data engineering.
Data Engineering Job Prospects
Once you have cracked the data engineer interview, where do you go? The good news is that the future of a data engineer looks extremely promising, given that the global data market is believed to grow to $115 billion by 2023. Moreover, a whopping 76% of businesses are keen on increasing their data analytics expertise in the coming few years (GeeksforGeeks). Some of the key industries where data engineers can build a thriving career include:
- Healthcare and medicine
- Construction
- Retail
- Education
- Communication and entertainment
- Energy and utilities
Additionally, data engineers can work with tech companies to design and develop various data systems and reporting tools for the end-users. The exact job profile of a data engineer varies depending on the size of the organization and the scale of data organization and management.
For instance, if you are working for a small company, you may be responsible for end-to-end data flow, right from collecting and configuring the data to managing the analytical tools. In contrast, if you are working for a large enterprise with complex data needs, the primary responsibility may be to create analytics databases and fill in the relevant information.
What’s the Interview Structure Like for Data Engineers?
Typically, the data engineer interview process consists of the following rounds:
- Phone screening: The first round evaluates whether you are the right fit for the company before the hiring managers meet you in person. Phone screening is usually with HR and a technical member of the staff.
- Take-home tests: If you clear the phone screening round, you may be invited for the next round, consisting of a take-home coding challenge.
- In-person or on-site interviews: Once you crack the assignment, the hiring managers are ready to meet you. There are multiple rounds of on-site interviews with various committee members. For example, Amazon has dedicated rounds on data modeling and SQL, where you are required to solve complex questions. Usually, a behavioral round is also part of the on-site interview round, during which the hiring managers assess your soft skills, self-awareness, and leadership abilities.
Interview Study Guide for Data Engineers
Data engineer interview questions cover a wide range of technical topics. Here are a few key areas you need to focus on when preparing for the interview:
- Database systems (NoSQL and SQL)
- Java, Python, and Scala programming languages
- Data APIs
- Data structures and algorithms
- ETL tools
- Database design
- Machine learning
- Data warehousing solutions
- Data architecture and big data technologies
- The basics of distributed systems
Based on the experience of former candidates and hiring managers, we have also created a study guide to boost your preparation. Make sure to go through this list carefully and track your progress as you complete each segment:
SQL
SQL questions are extremely common during data engineer interviews. While some questions may need an aggregation with a filter, others may need a few joins, recursions, and analytic functions. Following are a couple of sample SQL interview questions:
1. Analyze the given data on employees and departments of a company:
a) Employees:
Columns: id, first_name, last_name, salary, department_id
Types: int, varchar, varchar, int, int
b) Departments:
Columns: id, name
Types: int, varchar
From the above data, pick out the top 3 departments with a minimum of 10 employees and rank them as per the percentage of employees earning a salary of over $100,000.
2. You’re given a dataset of a company’s employees and departments:
a) Employees
id – int
first_name – varchar
last_name – varchar
salary – int
department_id – int
b) Department
id – int
name – varchar
Using this information, write an SQL query that selects the engineering department’s second-highest salary. Furthermore, your query should select the subsequent highest salary if more than one individual earns the highest salary.
Databases, ETL, and Data Warehouses
You can be asked to design a database/ETL for:
- Bicycle rental service
- Dating app
- Streaming app
- Job search website
- Udemy-like website
Operational Programming
These questions are focused on workflows and businesses processes. To solve them, you must know how to use arrays and dictionaries. Following are examples of problems you can expect:
- Given a string and substring, find the number of times the substring occurs in the string.
- Given a set of N words, where some words may be repeating. Count the number of occurrences of each word. (Order of the output must be the same as the input.)
System Design Questions
Although these questions aren’t very common, it’s good to brush up on your skills. Following are a couple of sample questions:
- Design a chatting application like Whatsapp
- Design a ride-sharing application like Uber
Algorithms and Data Structures
These are at the heart of every data engineer interview process. You can attempt the problems below to assess your strengths and learning:
You should also focus on revising core concepts such as:
- Data Structures: Linked Lists
- Data Structures: Trees
- Data Structures: Heaps
- Data Structures: Hash Tables
- Data Structures: Stacks and Queues
- Algorithms: Graph Search, DFS, and BFS
- Algorithms: Binary Search
- Algorithms: Recursion
- Algorithms: Bubble Sort
- Algorithms: Merge Sort
Other Data Engineering Interview Questions
In addition to the above-listed type of questions, you can also expect the following more generic questions during the interview:
- How do you create reliable data pipelines?
- What experience do you have with data modeling?
- What are the data engineering platforms you are most familiar with, and how did you use them in your previous jobs?
- Which computer languages are you fluent in?
Related reading: Facebook Data Engineer Interview Questions
Books for Data Engineering Interview Prep
Certain books can also help you to take your prep to the next level. We have handpicked a few titles that our alums also recommend:
- Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema – Lawrence Corr
- The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling – Ralph Kimball
- The Data Engineering Cookbook – Andreas Kretz
- Learning Spark – Holden Karau
- Spark: The Definitive Guide: Big Data Processing Made Simple – Bill Chambers
- Big Data: Principles and Best Practices of Scalable Realtime Data Systems – Nathan Marz
Tips to Crack Your Data Engineering Interview
- Practice your coding skills on a whiteboard instead of only using paper or IDEs that provide syntax support and familiar formatting. This will make you feel more comfortable when you face the actual interview, as you won’t feel like a fish out of water.
- Make sure to complete a couple of coding challenges to feel more confident during the technical rounds.
- Don’t forget to brush up on your soft skills. They are just as important as your technical mastery.
- If you have the slightest doubt about any questions during the interview, don’t hesitate to seek clarification. Remember, there is no such thing as a stupid question.
- While answering behavioral questions, resist the temptation of providing generic or scripted answers. Use the STAR method to structure your answers better and make it easy for the hiring managers to follow your chain of thoughts.
Land Your Dream Data Engineer Role!
Worried that your desire to become an ace data engineer will remain a pipe dream? Not if you enroll with Interview Kickstart!
At IK, 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. Our curriculum is one-of-its-kind and tailored to data engineers to help you crack the toughest tech interviews at FAANG+ companies.
Want to know more? Register for a free webinar and uplevel your career.
Data Engineering Career FAQs
Question 1: If I don’t have an advanced college degree, is it impossible for me to have a career in data engineering?
Absolutely not — no degree can prepare you for the real-world challenges that a data engineer faces. While software engineers may find it a lot easier to pick up the fundamental skills required for data engineering, nothing can match the experience you gain from learning on the job and creating a data pipeline right from the beginning.
Question 2: I am not an expert programmer. Can I still become a data engineer?
The primary job of a data engineer is to manage data. Most engineers rely on libraries or frameworks to take care of detailed programming. Having said that, you need to have a good grasp of the fundamental concepts of programming.
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