The Ultimate Data Engineer Interview Guide

If you are a data engineer, you must be eager to learn how to prepare for data engineer interview questions. Data engineering is an exponentially rising field, and top tech companies have abundant job opportunities for professional data engineers globally. You should know that top companies' acceptance rates can be as low as 0.2%, and it is better to be aware of the challenges ahead of you and prepare yourself accordingly. 

You must demonstrate your data engineering and soft skills while answering data engineer interview questions to outperform the competition and create a lasting impact on the recruiting panel. The following data engineer interview guide will help you ace your next technical interview and land your dream job at FAANG companies. 

If you are preparing for a tech interview, check out our technical interview checklist, interview questions page, and salary negotiation e-book to get interview-ready! Also, read Amazon Data Engineer Interview Preparation, Facebook Data Engineer Interview Questions, and Uber Data Engineer Interview Questions for specific insights and guidance on Data Engineering interviews at FAANG companies.

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Here's what we'll cover in this article:

• Understanding the data engineer interview process
• How to prepare for a data engineer interview
• Technical skills required to crack data engineer interviews 
• Top 5 tips to keep in mind on the day of the data engineer interview 
• FAQs on data engineer interviews 

Understanding the Data Engineer Interview Process

You should know the basic interview pattern to frame a strategic tech interview prep plan accordingly. A typical data engineer interview at top technical companies includes:

• The initial HR screen round includes basic questions around your experience, interest in the role, and the requirements of the role. 
• The technical phone screen will include a couple of behavioral questions and coding questions. The coding questions focus on data structures, mostly on arrays, trees, sorting, or linked lists. 
• The on-site interview will have three to four rounds that include:
  1. A round based on Python, SQL, and big data frameworks
  2. Two to three rounds on core data engineering concepts
  3. A behavioral interview round

You can learn in detail about the data engineer interview process in FAANG+ companies here. 

How to Prepare for a Data Engineer Interview

Here is a step-by-step guide on how to prepare for a data engineer interview. You must follow the below-mentioned guidelines to create a lasting impact on the recruiter. 

1. Create a Stellar Data Engineer Resume

Your resume is your first impression before the recruiters and hiring managers. You should be specific about the content of your resume and how you represent it. The following points are crucial for your job-winning data engineer resume: 

• You must only list the data engineering projects that you are ready to discuss in-depth with the interviewers. 
• The bullet points on your resume should demonstrate your skills, including technical competency, problem-solving, teamwork, and collaboration. You should follow the STAR (Situation Task Action Result) rule for bullet points in the work experience section. Most importantly, you must quantify your result as numbers catch the recruiter's attention. They showcase the scale and impact of your contribution to the project.

For example: "Developed a data pipeline using Airflow that led to process optimization and a revenue increase of 22%."

• You must include date engineer resume keywords from the official job description for ATS optimization.

Recommended reading: 15 tips for creating an ATS and recruiter-friendly resume. 

2. Practice Coding 

You must practice your coding skills on a whiteboard instead of only using paper or IDEs that provide syntax support and familiar formatting. This way, you will get comfortable with the actual coding interview rounds. You should be well-versed in basic and the most advanced problems. You can choose a programming language, such as R or Python, and begin with the basics, such as working on the syntax and commands for the particular language. 

Once you are thorough with the basics, progressively advance to algorithm design and development. You must practice some coding questions on programming websites like LeetCode or HackerRank to get comfortable writing code on a CoderPad.

3. Brush Up on Data Engineering Fundamentals 

While preparing for your data engineer interview, make sure you brush up on the fundamentals. You should be well-acquainted with SQL, data structure, and algorithms.  

SQL

It is a critical skill for data engineers, and most companies have an SQL interview in addition to a coding interview. As a data engineer, you are responsible for building reliable and scalable data processing and data modeling solutions. You should be adept at SQL and perform better than data analysts and scientists. 

Check out 50+ SQL interview questions for practice.

You should know that SQL is a data processing pattern shared by many big data frameworks, such as SparkSQL, pandas, KafkaSQL, in addition to being a query language. You should be proficient in translating complicated business questions into SQL queries and data models with good performance. You must understand how the query engine and optimizer work to efficiently write queries that process data. 

Data Structure and Algorithms

You should be prepared for the following essential data structures and algorithms topics that regularly feature technical interviews at FAANG+ companies. 

1. Sorting algorithms — quicksort, merge, heap sort. 
2. Arrays, strings, and linked lists
3. Hash tables and queues
4. Recursion
5. Trees and graphs
6. Graph algorithms, including greedy algorithms
7. Dynamic programming

4. Familiarize Yourself With the Most-Anticipated Data Engineer Interview Questions

You must practice the commonly asked data engineer interview question on system design, data modeling, and Python.

System Design

System design data engineer interview questions are often the most challenging part of technical interviews. The interviewer can ask you to design a data solution from end to end, usually composed of three parts: data storage, data processing, and data modeling.

For instance, for data engineer interview interviewer questions like design a data warehouse from end to end, you must first ask follow-up questions to pin down the requirements. You have to choose the best combination of data storage systems and data processing frameworks based on those requirements. 

Python

Python is an object-oriented programming language with the exception of control flow. Python is important for data engineers because of its ease of use, strong typing, abundant third-party libraries, and simple syntax. Here are a few Python interview questions for the data engineer Apple interview and other Tier-1 tech companies.

For example, write a function to:

1. Find _bigrams and return a list of all bigrams from the given string.
2. Locate the left insertion point for a specified value in the sorted order.
3. Create a queue. Display all the members and the size of the queue.
4. Find its first recurring character in a given string using recurring_char. Return 'None' if there isn't a recurring character.
5. Find all combinations that equal the value N in a given list of integers.

Some theoretical Python data engineer interview questions include:

1. Which Python libraries would you prefer for data processing?
2. How would you use data smoothing?
3. What are the benefits of using NumPy?
4. State the difference between *args and **kwargs.
5. How is "is" different from "=="?
6. How is memory managed in Python?
7. Do dictionaries offer faster lookups than lists in Python? If yes, explain why.
8. How would you remove duplicates from a list in Python?

Recommended reading: Top Database Interview Questions You Should Prepare for Technical Interviews.

5. Take Mock Interviews to Prepare for Behavioral Interview Rounds 

You must practice answering the common data engineer interview questions for the behavioral rounds but avoid providing generic or scripted answers. The STAR method is the best approach to structure your answers to data engineer interview questions as this helps the hiring managers follow your chain of thought. 

You should practice via mock interviews for hypothetical situation-based questions that form an integral part of the final rounds of the on-site interviews.  

6. Learn About the Company and Interviewers

As you prepare for your data engineering interview, devote some time to learning about the company and the interviewers. You must conduct proper research and learn about the company's principles, projects, strategic decisions in the recent past, products, achievements, and current challenges. This knowledge will convey your genuine interest in working with them. 

Technical Skills Required to Crack Data Engineer Interviews 

Here is a list of top technical skills that will help you crack data engineer interviews. You can include these on your data engineer resume to show that you are a good fit for the potential job position:

• UNIX, Linux
• Knowledge of SQL, MySQL, NoSQL
• Proficiency in Postgres, relational databases
• ETL skills including SSIS, PowerCenter, SSRS, data stage 
• Knowledge of ELK Stack, APIs, Oracle, Tableau, Git, Snowflake. 
• Hands-on experience with big data technologies include Hadoop, Apache Kafka, Spark, Hive, Cassandra
• Familiarity with Google Cloud, GCP
• AWS cloud services: Redshift, RDS, S3, EC2
• Experience in stream processing systems such as Storm, MLib, Spark Streaming
• Data modeling for analytical systems
• Expertise in workflow management tools such as Luigi, Azkaban, Airflow
• Software engineering skills including Agile, Scrum
• Basic knowledge of Machine Learning, BI, Platform Engineering
• Strong coding skills in Java, Python, Ruby, Scala, C, C++, C#, .Net, Perl, Golang, SAS, MatLab, or R.

You will also require a set of soft skills for data engineering positions. The most sought-after soft skills are as follows: 

• You must possess strong analytical skills to handle unstructured data.
• Your expertise in project organization and management abilities can give you an upper hand over other candidates. 
• You should have experience in supporting and working across teams. Teamwork abilities are a prerequisite for your job role because you will often work closely with data scientists and team members.

Learn more about what a data engineer does at FAANG+ companies and follow the guidelines mentioned above to stand out in your next data engineer interview. 

Top 5 Tips to Keep in Mind on the Day of the Data Engineer Interview

You should pay special attention to how you dress up for your interview and how you tackle the data engineer interview questions. The following tips will help you stand out in data engineer interviews.   

1. To succeed in the data engineering interview, you must exhibit a diverse skillset. 
2. While answering each question, you must take your time to demonstrate analytical and problem-solving skills effectively. Your answers should reflect your rational mindset and critical thinking abilities. 
3. You must ask a few questions as interviewers prefer hiring date engineers who are forthright in learning more about the company and the role.
4. During the coding interview, you must think out loud to let the interviewer know about your approach when solving a problem.
5. For the coding round, select a programming language that you are proficient in. 

Learn more about how to pitch yourself as a must-hire at a FAANG interview here. 

FAQs on Data Engineer Interview

1. How should I answer the situational data engineer interview questions?
   You should be prepared for the most common situational data engineer interview questions. These help the interviewer judge your character and test your problem-solving abilities under pressure. Talk about your notable achievements under dire circumstances at your previous jobs. You can precisely explain the problem, how you identified the cause, your course of action, and how that helped your company generate increased output.

2. Are data engineer interview questions hard?
   You should know that interviewees rate data engineer interview questions as medium-hard. They can be challenging, and it is not always easy to tackle technical data engineer interview questions. However, if you brush up on the basic concepts and practice the most crucial data engineer interview questions well, you can nail the most demanding rounds. 

3. Is coding important for data engineer interview questions?
   Your coding knowledge enables you to easily manipulate and clean the data you work with every day. For data engineer interview questions, you need to understand how to program in at least one language, such as Python, JS, or C++. Top companies have at least one coding interview round to check your ability. 

4. What is the annual salary of a data engineer?
   The average data engineer salary is $122,966 annually and $63.06 per hour in the United States (Talent.com).

5. How should I research the data engineer position I am applying for?
   Scan the job description carefully to understand everything the company seeks in the data engineer position. Visit the company website, go through their “About Us” page, and learn about their values, employee benefits, leadership, products, and more. Also, check out the company's YouTube channel and research employees on LinkedIn.

Gear Up for Your Next Data Engineer Interview

At Interview Kickstart, we have helped software engineers, software developers, and engineering managers upskill and land top-notch offers at FAANG and Tier-1 tech companies with our tech interview prep programs. Our reviews will tell you how we've shaped the careers of thousands of professionals aspiring to take their careers to new heights. Our courses are professionally designed and taught by a team of instructors comprising actual FAANG hiring managers and tech leads. 

Enroll in the Data Engineering Interview Course and learn how to develop skills to pursue a career path as a data engineer. You can nail your next Data Engineering interview at FAANG and Tier-1 tech companies with guidance from our experts.

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