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Data Engineer Interview Questions

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Data Engineer Interview Questions

Data engineers are IT professionals who are needed in almost every industry. Data engineers monitor data trends to determine best next steps for companies. A critical part of a data engineer job is to process raw data into usable data by creating data pipelines and building data systems.

Top Data Engineer Interview Questions & How To Answer

Question 1

Question #1: Can you describe in detail your level of expertise with programming languages?

How to answer
How to answer: Before the interview, review your resume and/or portfolio and make a list of the programs you are most proficient with. If you find that you are lacking the expertise in a program that the company predominately uses, describe yourself as a highly motivated self-starter who will work tirelessly to learn the program(s).
Question 2

Question #2: Explain data engineering in your own words.

How to answer
How to answer: Highlight your role in relation to the larger organization and other roles like data scientists to clearly define your contribution to the overall system of business. Clarify the difference between a database-centric engineer and a pipeline-centric engineer.
Question 3

Question #3: Can you describe your experience working with Apache Hadoop and cloud data management environments?

How to answer
How to answer: Research the company's software, data cloud products, and use of Apache Hadoop to be prepared for this inquiry. Data Engineers must be fluent in programming languages and data management systems used throughout the industry such as Apache Hadoop.

20,235 data engineer interview questions shared by candidates

About project , architectures ,some basics like partition,bucketing,RDD, Data frames, DAG execution engine, why from Hive to Spark SQL, difference between RDD, DataFrames, Datasets, how to make joins between data frames, what to do in spark job if our infrastructure is limited.
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Data Engineer

Interviewed at Capgemini

4.2★
Nov 30, 2020

About project , architectures ,some basics like partition,bucketing,RDD, Data frames, DAG execution engine, why from Hive to Spark SQL, difference between RDD, DataFrames, Datasets, how to make joins between data frames, what to do in spark job if our infrastructure is limited.

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