Data Engineer Test - Assess critical data engineering skills and knowledge

Mercer | Mettl Data Engineer Test is a pre-employment assessment used by managers and recruiters to screen and assess applicants and identify top candidates for data engineering roles in an organization.

What is the importance of the Data Engineer Test?

Organizations depend on the specialized abilities of data engineers to conceptualize, build, and maintain systems and infrastructure needed for the efficient processing and storage of large datasets. They play a critical role in ensuring the performance, scalability, and reliability of databases and data pipelines while optimizing data storage, retrieval, and distribution methods. Hiring data engineers is of utmost importance as it empowers organizations to leverage their data entirely, providing essential technical expertise and the required infrastructure for data analysis while mitigating potential risks associated with data-related challenges and errors. The Data Engineer Test holds significant value in the hiring process. It aids employers in identifying the most qualified candidates, allowing employers to shortlist applicants with the necessary skills or experience. It facilitates the selection of the most suitable talent, streamlining the hiring process and maximizing the potential for a successful outcome.

What is inside this Data Engineer Test?

Crafted by domain experts, this sixty-minute test includes nineteen MCQs and a coding challenge that serves as a litmus test for candidates competing for roles in this field. The required experience level is four to six years.

What skills does the Data Engineer Test cover?

• SQL: The SQL section of the test includes questions related to the following skill sets - queries, joins, sorting, and data definition language (DDL) commands.  
• Data modelling: The data modelling section of the test covers questions about the following skill areas - ER model, dimensional model concepts, normalization, and UML concepts.  
• Data warehousing: The data warehousing section of the test includes questions related to the following skill domains - data design, data integration, dimensional modelling, and data modelling.  
• Python 3: The Python 3 section of the test contains questions concerning the following skill areas - Python 3 functions, classes and operators, object-oriented programming (OOPS) concepts, and programming.  
• Hadoop: The Hadoop section of the test includes questions that pertain to the following skill domains - general knowledge, HDFS, and MapReduce.  
• Hands-on programming: The hands-on programming section of the test features questions related to Python 2 and 3 via Codelysis, a powerful simulator.

What roles can you assess when using the Data Engineer Test?

• Senior data engineer  
• Data engineer  
• Software data engineer

What competencies does the Data Engineer Test help assess?

This test covers crucial competencies for success in data engineering, including SQL proficiency, data modelling acumen, data warehousing prowess, Python programming skills, and a firm grip on Hadoop technologies.

How does a Data Engineer Test help recruiters hire people?

This assessment enables hiring managers to make unbiased hiring decisions and assemble a team of skilled data professionals by evaluating a candidate's expertise in data engineering tools and technologies. The test structure focuses on assessing candidates' understanding of SQL concepts, data modelling and warehousing fundamentals, and proficiency in Hadoop and Python and includes a Python coding exercise. Implementing this test simplifies and streamlines the hiring process for data engineers, ensuring that only the most suitable candidates secure these critical positions. This assessment is essential in determining whether applicants have the technical abilities to excel in the data engineer role. It emphasizes the importance of selecting the right data engineer, as this decision can significantly impact the success of an organization's data-driven projects.

Sample questions and answers for the Data Engineer Test

1. Which of the following tasks is not a part of data engineering?  

a) Data collection  

b) Data visualization  

c) Data transformation  

d) Data storage  

Answer: b) Data visualization

2. Which tool is commonly used for data integration in data engineering?  

a) Apache NiFi  

b) Amazon S3  

c) Microsoft Excel  

d) Google BigQuery  

Answer: a) Apache NiFi

3. What is the process of orchestrating complex data pipelines in data engineering?  

a) Data transformation  

b) Data governance  

c) Data pipeline orchestration  

d) Data visualization  

Answer: c) Data pipeline orchestration

4. What is the purpose of a data warehouse in data engineering?  

a) Real-time data processing  

b) Data storage for business analytics  

c) Data transformation for machine learning  

d) Data visualization for stakeholders  

Answer: b) Data storage for business analytics

5. Which technology is used for managing and scheduling data processing workflows in data engineering?  

a) Apache Spark  

b) Amazon Redshift  

c) Apache Airflow  

d) Google BigQuery  

Answer: c) Apache Airflow