This exam is meant to demonstrate your knowledge of databases, data processing, as well as your programming skills in the language of your choice.
The pairing phase, which should be viewed as a cooperative effort, is meant to give us an idea of what it will be like to work together.
We have included example data and programme code. The example schema generates a straightforward table and includes sample code for loading data from a CSV file and writing it to a JSON file in a number of popular programming languages. To use the examples, launch the database, and use the Docker containers, follow the instructions at the bottom of this document.
There are a number of steps that we need you to take. We anticipate this will only take a few hours of your time.
To demonstrate how to handle a straightforward data ingest and output, we have provided an example schema and code.
Below are instructions on how to use the example schema and code as well as run and connect to the database.
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All Interview Questions
- What are windowing functions?
- What is a stored procedure?
- Why would you use them?
- What are atomic attributes?
- Explain ACID props of a database.
- How to optimize queries?
- What are the different types of JOIN (CROSS, INNER, OUTER)?
Top 10+ Data Engineer Interview Questions and Answers
What are the main features of Apache Spark?
Main features of Apache Spark are as follows:
What is a Resilient Distribution Dataset in Apache Spark?
Apache Spark’s Resilient Distribution Dataset (RDD) is an abstraction of data. It is a resilient distributed collection of records split among several partitions. RDD hides the data partitioning and distribution behind the scenes. Main features of RDD are as follows:
For updates, join our slack workspace and follow me on LinkedIn (dkisler).
How will you improve the performance of a program in Hive?
A Hive program can be made to perform better in a variety of ways. Some of these include the following: Data Structure: When writing a Hive program, we must choose the appropriate data structure for our needs. Standard Library: We should use standard library methods whenever possible. Standard library methods perform significantly better than user implementation. Abstraction: Occasionally, excessive abstraction and indirection can make a program run slowly. We should remove the redundant abstraction in code. Algorithm: Using the proper algorithm can significantly alter a program. In order to solve our problem with high performance, we must locate and choose the best algorithm.
FAQ
What questions are asked in Data Engineer interview?
- 1) Explain Data Engineering. …
- 2) What is Data Modelling? …
- 3) List various types of design schemas in Data Modelling.
- 4) Distinguish between structured and unstructured data. …
- 5) Explain all components of a Hadoop application. …
- 6) What is NameNode?
How can I pass data engineer interview?
- Create a Stellar Data Engineer Resume. …
- Practice Coding. …
- Brush Up on Data Engineering Fundamentals. …
- SQL. …
- Data Structure and Algorithms. …
- System Design. …
- Python. …
- Take Mock Interviews to Prepare for Behavioral Interview Rounds.
