Data Engineering Interview Questions and Answers 2022

Data science is going to be one of the most promising career opportunities. Its present growth and promising future are backed by stats that show an exponential rise in the demand for data scientists across the globe. One must be prepared and qualified to be placed in some of the premium organizations.

Choosing the right data Science course will give you an upper edge in understanding all the key concepts of data science and its applications. In addition to this, it is equally important to prepare for the interview.

The interview round can be a bit challenging. Data engineer process interview questions can be tricky. Hence, as much as you prepare for qualifying for the best data science certification course, it is equally important to prepare yourself for the data engineering interview questions and answers.

Knowing the right data engineering questions and answers will ensure you are confident in the interview. This blog takes you through a series of Data engineering technical interview questions and answers. While there are many aspects that you need to prepare yourself. But to buckle yourself up, you can begin with the sets of data engineering interview questions and answers.

Table of Contents

Data engineering interview questions and answer round

The entire interview is divided into two sections:

Generic interview– Here the interviewer will ask about the general overview of your personality, profile, work experience and others.
Technical round– It has technical Data engineering interview questions and answer. The following sections takes you through a detailed overview of the Data engineering interview questions and answer.

Important General Data Engineer Interview Questions and answers

1. Generic round of data engineering interview questions and answer
  1.1 What makes you suitable for this data science job profile?
  The first round of the interview is usually telephonic; if you can qualify this round, the interviewer will call you for one-to-one interaction. In such a case, the interviewer would have gone through your profile in-depth and seen certain qualities that match the skill set required for the particular profile.
  
  Hence your first step should be to review the company and check its website and the projects they have handled. You must also prepare yourself with some practical aspects of data science as well as its recent applications and examples.
  
  So, when the interviewer asks you these questions, you have to answer about your skill sets and how you will use the skill set to leverage it for the benefit of the company.
  
  1.2 What are the roles and responsibilities of a data engineer?
  The answer to this question can be very expansive, but when you are sitting in an interview, then you have to be precise in the information. Hence you can include the following points in your answer:
  - Development, testing and maintenance of database
  - Developing, validating and maintaining data pipelines
  - Data acquisition
  - Working in adherence with data governance and security guidelines

Technical Round of data engineering interview questions and answer

1. Data Engineer Process Interview Questions
  2.1 Can you explain the process that you adopt for the completion of the project?
  In this question, the interviewer can also ask, “Walk me through a project you worked on from start to finish.” The interviewer is asking this question to understand your approach, your thinking skills, your problem-solving skills and how well you understand a particular question. If you have worked on a data engineering project as a student or a professional, you should be able to explain the entire process in detail to the interviewer.
  
  Remember, before answering this question, you must prepare yourself well for a particular project that you have handled. When it comes to a project, usually in an organization, a team works on it, but when you are sitting in an interview, it is important that you should know and be an expert on every aspect of the project.
  
  To begin answering this question, you can explain what the problem was or what the case study that you were solving. Follow this question with a detailed step-by-step breakdown of the process you adopted to access raw data and how you convert it into structural data. This involves cleansing data and filtering out the information that will be useful for solving a particular business problem.
  
  Individuals who have worked on several projects can often get confused about this question. Hence, in that case, you can prepare yourself for 3 to 4 different projects and thoroughly study them. You can also read project documentation and understand the problem statement before presenting the answer to the interviewer.
  
  As a part of this question, you should be able to explain to the interviewer the various tools that you have used and why. For example:
  - GCP, Docker and Terraform are used for the cloud environment
  - Spark is used for batch processing
  - Kafka, along with Spark, is used for data streaming
  - Airflow and BigQuery for storage of data

We want to highlight here that you should be thorough with every tool and how and why it is used for a particular step.

Junior data engineer interview questions
This data engineering interview questions and answer revolve around the tools used in data science, coding and SQL.

3.1 What is Data Modelling, and what are the different design schemas used in Data Modelling?
It is a method of documenting complex software designed in the form of an easily comprehensible diagram. There are two main types of schemas and data modelling these are:
- Star schema– It has this name because of its appearance like a star. This schema is used for acquiring a large volume of data sets. In this case, there is a centre table and a fact table, and it is associated with different dimension tables.
- Snowflake schema– This is the further expansion of the star schema.
3.2 Which ETL tools do you prefer using and why?
This can be a tricky question. Hence you should be very precise in answering it. You must only mention the tools which you have mastered. But at the same time, you must also have some information on the different ETA and tools so that you can explain your reason for selecting one particular tool from the list of others. Some of the popular tools that are used here are Kafka, Airbyte, and dbt.
Data engineer manager interview questionsFor this profile, the interviewer will check your technical skills, problem-solving skills, leadership skills and decision-making capacity.4.1 How is data warehousing different from an operational database?
Data Warehouse
It is a storehouse of historical data. It supports high-volume analytical processing. The purpose of designing a data warehouse is to load high-volume queries.

Operational Database Management Systems– These are used to manage dynamic databases in real-time. It is information regarding the day-to-day operations of the business.

4.2 Do you think a company should emphasise a disaster recovery plan for a data system?
Every organization must be ready for disaster management when working in a virtual system. The data engineer plans and prepares the disaster recovery process for the data storage system. It involves backing up the data and files. This data could be retrieved in case of a cyber-attack or data breach attempt.
Data Engineering Tools

5.1 What are some of the best data engineering tools of the present time?
- Airflow
- Amazon Redshift
- Apache Spark
- Apache Hive
- Big Query
- Dbt
- Looker
- Tableau
- Segment
- Snowflake
There are several other tools as well that you can answer this question. In addition, you should also remember the tools that you are mentioning should be popularly used. At the same time, you must know about these tools and their applications.
Python interview questions for data engineers
6.1 What are some of the best data engineering tools of the present time?

It is an automated method to extract a large volume of data from a website. Usually, the information on the website is unstructured. Web scraping allows the data science professional to collect this unstructured data and store it in a structured format. There are different ways of doing it. You can use online services or write your code. Let’s understand how you implement web scraping in Python.

To extract data using web scraping with Python, you need to follow these basic steps:
- Choose a website that you want to scrape
- Now start with the website inspection
- Decide on the data you want to extract
- Extract the data and structure it by cleaning it using Pandas and Numpy
- Begin with writing the code
- Now run the code and extract the data
- Store this data in the desired format
SQL interview questions for data engineers
7.1 What are the different objects created by creating a statement in MySQL?

The following objects are created in the create statement in MySQL:
- Database
- Event
- Function
- Index
- Procedure
- Table
- Trigger
- User
- View
7.2 How can you see database structure in MySQL?

For this, you have to use the DESCRIBE command. The syntax for this is: DESCRIBE Table name;
FAANG Data Engineer QuestionFAANG is an acronym referring to the five most popular and best-performing American technology companies like Facebook, Amazon, Google, Netflix and others.8.1 Facebook Data Engineer Interview Questions8.1.1 What is the benefit of Kafka?
- It has multiple brokers for data distribution
- It is highly scalable
- Apache Kafka clusters avoid delay, and so enhance productivity
8.2 Amazon Data Engineer Interview Questions

8.2.1 If you have an IP address in the form of a string, then how would you find whether it is a valid IP or not?

For this, you need to split the string on “.” and create multiple checks. This is used to find the validity of the IP address.