Data Engineer Test for Recruitment
Data Engineer test evaluates a candidate's proficiency in Hadoop, R, Mongo DB, SQL, Data Modeling and Data Warehousing. The data engineer assessment evaluates Data Engineers who are responsible for creating reports, dashboards, data pipelines, and optimizing Python code to run it in C or Java.
Availability
Ready to Use
Test Type
Coding
Experience Level
1-3 years
Difficulty Level
Moderate
Test Duration
35 Minutes
Total Questions
25 MCQ
Relevant Job Roles
Data Science Engineer (using R Programming), Big Data Engineer (using R Programming)
Scores Reported
English
Inside This Assessment
The Data Engineer assessment from Mercer | Mettl is used to assess a candidate's skills in applications and harvesting of huge data. The test also evaluates their proficiency in creating interfaces and mechanisms for the flow and access of information.
Designed by subject matter experts, this 35-minutes test includes 25 MCQs to test the cognitive abilities of an applicant. This Data Engineer test evaluates a candidate's proficiency in Hadoop - Hive, Hadoop - Spark, R-programming, MOngo DB, SQL, Data Modeling and Data Warehousing. The mentioned skills of the candidate are measured on three levels; basic, intermediate and advanced.
Key profiles this Data Engineer test is used for:
- Data Science Engineer (using R Programming)
- Big Data Engineer (using R Programming)
SKILL LIBRARY
This Assessment is a part of following Skills Libraries
Data Engineer Competency Framework
Get a detailed look inside the test
Competency Under Scanner
Competencies:
Hadoop - Hive
This Data Engineer assessment evaluates Hadoop - Hive - Application on basic, intermediate and difficult level.
Hadoop - Spark
This Data Engineer assessment evaluates Hadoop - Spark - Application & Concept on basic and intermediate level.
R Programming
This Data Engineer assessment evaluates the following subskills in R-programming; R - General - Application, R - Functions - Application and R - ggplot2 - Application.
MongoDB
This Data Engineer assessment evaluates the following subskills in MongoDB - Aggregation - Application, Basics - Application, Indexing - Application and JSON Query - Application.
SQL
This Data Engineer assessment evaluates the following subskills in SQL; DDL Commands - Application, DML Commands - Application, Joins - Application and Sort - Application.
Data Modeling
This Data Engineer assessment evaluates the following subskills in Data Modeling; ER Model - Application, Normalization - Concept, Techniques Tools and Implementation - Application and UML - Concept.
Data Warehousing
This test assesses the following subskills in Data Warehousing: Data Design - Application, Data Integration - Application, Dimensional Modeling - Application and OLAP - Relational - Analysis.
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Frequently Asked Questions (FAQs)
1. How do I prepare for an interview for a data engineering role?
The majority of the questions centers on a candidate’s understanding of data warehouses, ETL development, scripting, and NoSQL.
Here are a few questions that might come in handy if you are preparing for an interview:
What would be your approach to develop a new analytical product?
Is there any difference between a data warehouse and an operational database?
Can you tell us about a time when you faced issues with an ETL, and how did you handle it?
Do you have experience in PowerShell, Bash, Java, Python?
That’s the long and short of it. Even though we have included conceptual questions, what matters most is your expertise in SQL, Python, and R, etc.
2. Can candidates be benchmarked based on the internal sample set?
Yes, at Mercer| Mettl, it can be done. Please write to us if you seek further information; we will be happy to assist you.
3. Is it possible to customize the report as per the need?
Yes, at Mercer|Mettl, it can be done. Should you need any further information, please write to us, and we will be happy to assist you.
