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The demand for data engineers has risen significantly recently, and this is because they are considered the backbone of data science and engineering. They help modern businesses analyze their data, build predictive models and develop software that is important for the growth and maintenance of modern companies.
Data engineers use and manipulate, process, and maintain data in ways that will be reliable, usable, and accurate by businesses. In more technical terms, data engineers build, process, and maintain data flow across a business.
Why Do You Need To Prepare For An Interview?
Regardless of your experience, you must go to an interview well prepared if you aim to land the job. A good way to prepare for the interview is to study commonly asked questions in data engineer interviews.
During the interview, you are expected to think and answer questions on the fly, and not many people know how to communicate what they already know to others. This is another good reason you should prepare very well before the interview.
Also, going to an interview knowing that you are prepared with a certain level of confidence also positively affects your chances of acing the interview.
What Are The Possible Data Engineer Interview Questions?
While studying for your data engineer interview, you must understand the different questions that may come up in your interview. There are two main types of questions that you will encounter in your interview. They are:
Generic: These interview questions help the interviewer learn about your thought process, attitude towards co-workers, and even your work ethic.
Domain-specific questions will test your k knowledge and experience and evaluate your qualification for the role you applied for.
What Is The Difference Between Data Engineers And Data Scientists?
People often confuse data engineers and data scientists as being the same. Both data engineers and data scientists are involved in handling data and making it sound at companies and working closely on big data projects, causing them to overlap between the two roles.
The two roles are different as they are concerned with different core responsibilities, even though they work together to achieve a common goal.
A significant difference is that data engineers build the data infrastructure data scientists use. Data engineers keep the systems robust and secure; they are trained to handle and process a vast amount of data while being efficient.
Top 20 Data Engineer Interview Questions
Below is a list of the most common data engineer interview questions arranged in no particular order:
1. Why should we hire you? What do you know about our business?
This comes as a general question in most interviews. Interviewers ask this question to know how motivated or passionate you are about working for the company. To answer correctly, you need to highlight your valuable experiences, skills, and personality that will help you excel in your career as a data engineer.
2. What Is Data Engineering?
This question evaluates your knowledge and understanding of the roles of a data engineer at the company. Your answer should outline the formal meaning of data engineering and your experience or views about the field of data engineering.
3. What is data modeling?
Data modeling is a scientific approach to documenting complex data systems using diagrams to build a pictorial or conceptual representation of the system. If you’ve had previous experience with data modeling, mention it to the interviewer while answering this question.
4. What are the design schemas in data modeling?
Your answer should briefly state the two main types of schemas in data modeling: Star schema and Snowflake schema.
Also, clearly explain each or any of them if you are asked to do so.
5. What are the core skills of a data engineer?
Although different companies have their definition of a data engineer and would judge candidates based on their requirements, there are skills you must possess to be a successful data engineer.
They include comprehensive data modeling, database design and architecture knowledge, working experience in data stores and distributed systems, data visualization, computing and math, communication, and leadership skills.
6. Why did you choose a career in data engineering?
Although this seems like a fundamental question, it is a general question that comes up in interviews regardless of your experience. This question helps the interviewer learn about your motivation and interest in pursuing a career in data engineering.
Companies want to hire individuals who are passionate about what they do, and you can use this question as an opportunity to share your story, motivation, and goals with the interviewer.
7. What are the essential frameworks and applications you use as a data engineer?
This question helps the interviewer know whether you know the critical requirements as a data engineer and have the required skills. Your answer should include the technical frameworks and applications used in data engineering, like SQL, Python, Hadoop, and more. You can share your experience using these tools and how they help you get things done.
8. What language do you use?
This question emphasizes the importance of scripting and scripting languages in data engineering. You must have a solid background in scripting languages to perform analytical tasks efficiently and automate your work.
9. What are the responsibilities of a data engineer?
This is one question the interviewer uses to discern if you understand the roles of a data engineer in a company and if you are a good fit.
You should clearly state a data engineer’s critical responsibilities, including developing, testing, and maintaining architecture, deploying machine learning models, data acquisition and development of data set processes, etc.
Further Reading: Data Engineer Job Description Template 2023
10. What was the algorithm you used on a recent project?
Here, the interviewer wants to know about the problems you solved in your recent projects, your approach to solving the problem, and why you solved the problem using your approach.
You can also talk about the algorithm you used, the scalability and efficiency of the algorithm you used, and the results you got.
11. Have you ever transformed unstructured data into structured data?
Interviewers ask this question to know what challenges you have handled with unstructured data and how you solved them.
12. Have you ever been involved in data modeling?
Here, the interviewer wants to know your experience with modeling data. A correct answer here will include your approach, the tools you used, and why you used them.
13. What is big data, and how is Hadoop related to big data?
Significant data results from exponential growth in data availability, storage technology, and processing power. Hadoop is a framework used to handle large volumes of data in the extensive data ecosystem. You can also mention the components of Hadoop if you want to.
14. What is a NameNode, and what are the implications of a NameNode crash?
A NameNode stores metadata about nodes, size of files, hierarchy, and bits of information of different kinds. One implication of a NameNode crash is the non-availability of data.
15. What is a Block, and what role does a Block scanner play?
A Block is the most straightforward unit of data allocated to a file which is automatically created by the Hadoop system for storage in different nodes in a distributed file system. A Block scanner verifies a data node’s integrity by checking its data blocks.
16. How would you validate data migration from one database to another?
There is best to discuss how your utmost priority as a data engineer is to validate and ensure no data is lost. This allows the interviewer to understand your thought process on how validation works.
This question requires you to talk about validation types in different scenarios.
17. Have you ever worked with ETL? If yes, discuss which one you prefer the most.
ETL stands for Extract Transform Tool. This question is used to evaluate your understanding of ETL tools and processes. In your answer, you should be able to list all the properties that make a tool stand out and your preferences. This helps you to show your experience in the ETL process too.
18. What happens when a Block scanner gets corrupted by a data block?
This is a popular data engineer interview question used to evaluate an individual’s knowledge and experience in data engineering. Your answer here should clearly state all the steps a Block scanner follows when it finds a corrupted data block.
19. Which Python libraries do you use for proficient data processing?
This question demands you to know the basics of the python programming language as it is the most used language among data engineers.
You are expected to briefly talk about how you use python libraries like NumPy to process arrays of numbers and pandas to prepare your statistics and machine learning works. Also, you should know the importance of using these libraries in case the interviewer asks.
You can learn about the Free Online Python Course Certification in 2023
20. What is the difference between Lists and Tuples?
This question is used to evaluate your understanding of the python programming language. Both Lists and Tuples are some basic data structures in python, but the difference between them is that while Lists are mutable (i.e., can be modified), Tuples are immutable (i.e., can’t be changed). You can use examples to show your understanding here with some examples.
Conclusion
Though data engineering might sound like a boring routine job, it has many facets. These interesting facets of data engineering are clear from the questions that are asked in interviews.
If you are serious about starting a career as a data engineer, you must prepare very well and be ready to answer the questions.
Once you understand the essential concepts of data engineering, you will answer the questions listed above, ace the data engineer interview, and land the job you deserve.
Frequently Asked Questions (FAQs)
How should i prepare for this interview?
To prepare for this interview, you must review engineering books, courses, and articles, practice random questions from readers, do easy Leetcode problems, etc.
Is data engineering lucrative?
Yes, of course, data engineering is a brilliant and one of the highest paying careers.
Why do i need Python programming language for data engineering
The Python programming language is the most popular option among data engineers, so go ahead and learn python.
When should i learn python?
There is no fixed time to learn python as the time varies and depends on many factors about the individual. On average, a lot of data engineers believe it takes six months.
Is data engineering lucrative?
Data engineers are currently among the most sought-after individuals in the job market. Don’t forget you have to be skilled first.
Is data engineering interview challenging?
The data engineering interview is quite challenging, but with adequate preparation, you can ace the interview.
Is math relevant in Data Engineering
Yes, math and computing skills are very relevant in data engineering.
References
Recommendations
Frequently Asked Questions (FAQs)
How should i prepare for this interview?
To prepare for this interview, you must review engineering books, courses, and articles, practice random questions from readers, do easy Leetcode problems, etc.
Is data engineering lucrative?
Yes, of course, data engineering is a brilliant and one of the highest paying careers.
Why do i need Python programming language for data engineering
The Python programming language is the most popular option among data engineers, so go ahead and learn python.
When should i learn python?
There is no fixed time to learn python as the time varies and depends on many factors about the individual. On average, a lot of data engineers believe it takes six months.
Is data engineering lucrative?
Data engineers are currently among the most sought-after individuals in the job market. Don’t forget you have to be skilled first.
Is data engineering interview challenging?
The data engineering interview is quite challenging, but with adequate preparation, you can ace the interview.
Is math relevant in Data Engineering
Yes, math and computing skills are very relevant in data engineering.
References
- interviewquery.com/p/data-engineer-interview-questions
- guru99.com/data-engineer-interview-questions.html
- projectpro.io/article/data-engineer-interview-questions-and-answers/456
- whizlabs.com/blog/big-data-interview-questions/
- softwaretesttips.com/data-engineer-interview-questions/
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