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15 Skills to Ace Data Engineering Interviews

Posted on 
March 16, 2022
|
by 
Team Interview Kickstart

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You can nail data engineering interview questions if you have skills in numerous programming languages and have a strong problem-solving background. Data engineering is one of the fastest-growing fields. Top companies, such as Facebook, Google, Amazon, Apple, and many others, seek to employ proficient data engineers who can handle their complex data properly and efficiently. 

The demand for data engineers is up by 50%, and there is a shortage of skilled data engineers. So, this is the opportunity for you to grab the top spot by cracking your data engineer interview. Read on to discover the secrets of landing a successful data engineer job with some must-have skills to ace the technical interviews at FAANG+ companies. Learn how to prepare for data engineer interview questions and outperform the competition. 

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This article will look at the top skills to ace data engineering interviews at top FAANG+ companies. Here's what we'll cover:

  • How to prepare for data engineer interviews
  • 15 skills to ace data engineering interviews
  • Data engineer interview preparation
  • Frequesntly Asked Questions on Data Engineer Interviews

How to Prepare for Data Engineer Interviews

Data engineer interviews in various technical and FAANG companies are conducted in three rounds — recruiter phone screen, technical phone screen, and on-site round. 

Recruiter Phone Screen Round

This will be your first telephonic screening interview for the data engineer position at any tech company. The interviewer will assess your knowledge of various programming languages and problem-solving skills. They might also ask a few coding questions. So, you must have solid fundamentals in Python, Java, SQL, and others to ace data engineer interview questions. 

Technical Phone Screen Round

In this round, you will be talking to a data engineer. The interviewer will ask questions about data warehousing, ETL, data modeling, SQL, data structures, joins, subqueries, aggregations, filters, case statements, and other related topics. You can also expect a few scenario-based questions to test your situational and behavioral skills

On-site Round 

This is the most challenging round; it consists of 3-4 sub-rounds. You can expect mixed questions ranging from data warehousing big data technology to real-life problems based on past projects. 

The interviewer will check your abilities and how you execute data modeling in SQL queries. They will also check how you influence peers, collaborators, and stakeholders in cross-functional roles. Lastly, HR will ask questions based on your previous projects and how you managed the difficulties as a data engineer, if any. 

Recommended reading: How to Prepare for Data Engineer Interviews

15 Skills to Ace Data Engineering Interviews 

If you’re wondering how to prepare for a data engineer interview, the skills below will help you gain confidence in mastering data engineer interview questions at any top-level company:

1. C++

It is a simple but powerful programming language. It is one of the most asked topics during data engineer interviews. You should know how to retrain the data and apply predictive analytics in real-time and other fundamentals to answer the questions based on C++. 

2. Scala

It is an extension of the Java programming language and is the most widely used tool by various tech companies. To crack a data engineer interview, you should learn Scala thoroughly. 

3. Python

This is the most common language and the most commonly asked topic in a data engineer interview. To build data engineering pipelines, you should know the list, set, dict, tuples, methods, class, inheritance, iterators, and other topics. 

4. Apache Kafka, Spark, Airflow, Hadoop

These have become one of the much-needed skills in the technology industry. Preparing questions based on Kafka, Spark, Airflow, Hadoop will help you land your next data engineer role.  

5. Hadoop Ecosystem

It is not feasible to store a wide range of complex data in traditional systems. Therefore, technical companies look for data engineers who are well-adapted to the Hadoop Ecosystem to handle their sophisticated data. 

6. Amazon Web Services/Redshift (Data Warehousing)

It is a relational database designed for query and analysis. It's designed for a long-range view of data over time. Most data engineer job descriptions specifically list AWS as a requirement. Therefore, you must prepare this topic thoroughly. 

7. Azure

It is a cloud technology that enables data engineers to build large-scale data analytics systems. You must be well-versed with the fundamentals of Azure, from data storage to advanced machine learning, to ace your data engineer interview. 

8. HDFS and Amazon S3

These are specialized file systems used to store data during processing. It has a wide variety of big data analytics. You must be acquainted with big data concepts to answer questions related to this topic. 

9. SQL Databases

It is crucial for a data engineer interview. The interviewer will give you an ERD and ask you to write queries to answer the analytical questions. You should know select, from, where, like, joins, window functions, and table relationships to answer data engineer interview questions based on SQL databases. 

10. ELK Stack

It is a collection of three products — Elasticsearch, Logstash, and Kibana. These three allow you to store, search and analyze a big volume of data. Thousands of companies use ELK, including Medium, Udemy, Slack, and others. 

11. Data Pipelines

The interviewer will involve you in a data pipeline design question. Once you finish designing, you will be asked to test, backfill, scale, handle bad data, resolve dependencies, and other similar problems. You must have clear data pipelines fundamentals to answer these data engineer interview questions. 

12. Distributed System Fundamentals

The questions are less commonly asked from this topic. However, you must also know about Apache Spark data storage and processing and Dremel (asked in Google data engineer interview questions).  

13. Cloud Computing

You must be familiar with this topic and others, such as cloud storage, compute, database, serverless functions, and other cloud services. 

14. Probabilistic Data Structures

Data engineer interview questions based on this topic are rarely asked. However, you must prepare questions like, 'what is an efficient way to count the number of distinct ids in a distributed system where some error probability is fine?'. To answer these data engineer interview questions, you should know about hyperlog, count min sketch, and bloom filter. 

15. System Design

Companies like Netflix, Twitter, and others, will ask standard system design questions in a data engineer interview. So, you should prepare these topics — sample batch ETL, sample streaming ETL, CDC, and others. 

Data Engineer Interview Preparation

If you are preparing for a data engineer interview, especially at FAANG, you must be geared up to face unique challenges like what kind of data must be selected, shaped, and processed. To do this competently is one of the most challenging jobs. 

Data engineers at FAANG work alongside product managers, designers, data scientists, software engineers and are an integral team. 

You should have a good command over database systems, such as SQL and other programming languages, to work on complex datasets. You should also have in-depth knowledge and experience with big data processing frameworks, such as ApacheSpark, Hadoop, and other analytical environments.

To help you with your interview prep, we’ve covered some interview questions asked at Data Engineer interviews at some of the FAANG companies:

Amazon Data Engineer Interview Questions

Here are a few Amazon data engineer interview preparation questions that will guide you to land your dream job:

  1. What is data modeling and what are the types of design schemas in data modeling?
  2. Explain the differences between structured and unstructured data.
  3. How would you develop an analytical product from scratch?
  4. Which ETL tools have you used? Tell us about your experience.
  5. How is Hadoop related to big data?
  6. Explain namenode. What happens in case of a namenode crash?
  7. Explain a block and block scanner.
  8. Explain is MapReduce in Hadoop and Reducer.
  9. How will you deal with duplicate data points?

Recommended reading: Amazon Data Engineer Interview Questions

Apple Data Engineer Interview Questions

To become a part of the data engineering team at Apple, you must be adept at creating critical, optimized pipelines and devise platforms that support customer analytics. You must have a profound knowledge of database management systems and other technologies, such as SQL, Hadoop, MapReduce, Spark, etc. You should also prepare behavioral questions to impact the recruiting team strongly. 

Given below are a few sample data engineer Apple interview questions for your practice:

  1. Should Spark be preferred over Mapreduce? Why?
  2. What is Monkey Patching?
  3. Explain the concept of a window function.
  4. Explain the importance and functions of AWS Redshift and Spark.
  5. How are Postgres and Redshift different?
  6. Why do you want to be a Data Engineer?
  7. Tell me about a time when you couldn't meet a deadline. What did you do?

Recommended reading: Apple Interview Questions

Google Data Engineer Interview Questions

A data engineer at Google is responsible for building the architecture and infrastructure for data generation. Here are some interview questions to help you with your interview prep:

  1. What are the differences between structured and unstructured data?
  2. Name the four Vs of Big Data.
  3. What are some of the design schemas used for data modeling?
  4. What are linked lists?
  5. State some of the uses of Hadoop.
  6. How does Big Data Analytics contribute to a company’s revenue?

Read How to Prepare for Your Google Data Engineer Interview for more information on Google Data Engineer interviews.

Python Interview Questions for Data Engineers

You must practice programming questions, especially beginner-level ones, to master hard skills for the data engineer interview. You should make coding challenges a core piece of your interview preparation strategy. 

Besides focusing on soft skills, i.e., solving problems efficiently, you must focus on how to solve problems within the allotted time frame with the correct problem-solving approach. You should not forget to study the commonly used structures and algorithms and must be comfortable answering them to the interviewer. 

Here are a few Python interview questions for data engineers for your practice to help you crack any technical interview at top companies:

  1. Write a function find_bigrams to take a string and return a list of all bigrams.
  2. Given a list of timestamps in sequential order, return a list of lists grouped by week (7 days) using the first timestamp as the starting point.
  3. Write a function to locate the left insertion point for a specified value in sorted order.
  4. Write a function to create a queue and display all the members and the size of the queue.
  5. What are some primitive data structures in Python? What are some user-defined data structures?
  6. What is data smoothing? How do you do it?
  7. When to use Python vs. Java?
  8. When would you use NumPy Arrays over Python lists?
  9. Given a dictionary consisting of many roots and a sentence, write a function replace_words to stem all the words with the root forming it. If a word has many roots that can form it, replace it with the root with the shortest length.
  10. Given a percentile_threshold, sample size N, and mean and standard deviation m and sd of the normal distribution, write a function truncated_dist to simulate a normal distribution truncated at percentile_threshold.
  11. What is the difference between "is" and "=="?
  12. What is the difference between append and extend in Python?

Frequently Asked Questions on Data Engineer Interviews

  1. What soft skills are required to ace data engineer interview questions?
    As a data engineer, you should have a handful of soft skills to perform your duties. Some of those soft skills include — communication skills, collaboration, and presentation skills. You must understand how to meet the expectations of the team. You must also communicate and collaborate effectively with your team members and understand the work to assess the problem and find an innovative solution.
  1. What educational background do the tech companies look for while recruiting data engineers?
    There are no formal data engineer qualifications as this field is relatively new. However, you must possess a bachelor's degree in mathematics, statistics, computer science, or other business-related fields. You must also have a certification in advanced statistics and programming languages that can be used to mine and query data. 
  1. How do I prepare for data engineer interview questions?
    To prepare for data interview questions, you should be well-versed in the technical aspects of various programming languages. You must have a strong command of coding challenges and learn how to crack them within the given timeframe. The interviewer looks for a candidate who has an in-depth knowledge of basics and has great communication skills. So, you must work on these skills to create a strong impact on the interviewer.
  1. What is the process of a data engineer interview?
    You must know the data engineer interview process takes place in three parts. The first one is the phone screen, in which you will be questioned about your experience. The second part is the take-home exam, in which you will be given coding challenges and timed problems. The last and the most important is the on-site interview. In this, the interviewer will ask questions about algorithms, data structures, and other related topics.
  1. How much money does a data engineer make?
    Data engineer salaries vary from company to company. The average salary of a data engineer is $116,499 per year. Netflix is the top company that offers $276,095 per year to its data engineers, followed by eBay, Grainger, Meta, and System Soft Technologies, which offer $178,867, $176,992, $174,502, and $171,239, respectively (Indeed.com).

Recommended reading: Google Data Engineer Salaries

Gear Up for Your Next Data Engineering Interview

If you're looking to start your preparation for data engineering tech interviews, we offer a one-of-its-kind Data Engineering Interview Course tailor-made for data engineers to crack interviews at the biggest companies.

Register for our technical interview webinar to get ready for an upcoming software engineer or software developer interview. At Interview Kickstart, we've trained over 10,000 engineers to land lucrative offers at the biggest tech companies. Our instructors, who are FAANG hiring managers, know what it takes to nail tough tech interviews at top technology companies.

Register for our FREE webinar to learn more.

WEBINAR +LIVE Q&A

How To Nail Your Next Tech Interview

Hosted By
Ryan Valles
Founder, Interview Kickstart
Our tried & tested strategy for cracking interviews
How FAANG hiring process works
The 4 areas you must prepare for
How you can accelerate your learnings

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