How to Assess Data Engineering Skills on HackerRank?

Overview

In this article, we unpack HackerRank enabled capabilities to assess Data Engineering skills. Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. At HackerRank, Data Engineering skills can be assessed through our pre-designed as well as custom-built tests with important skills such as SQL, Apache Kafka, Hadoop, Couchbase, Apache Spark, Java, Scala, among others. 

Before we proceed, to learn more on how we define the core competencies of the skills listed above, please visit here. 

Data Engineering questions help you assess candidates’ ability to think about scaling, Reading, and writing data using Data Frames, data transformation altogether. 

By using HackerRank’s Data Engineer Role, both theoretical and practical knowledge of the associated skills are tested. We classify our Data Engineering assessment into three roles, as follows: 

• Data Engineer (JavaSpark)
• Data Engineer (PySpark)
• Data Engineer (ScalaSpark) 

Skills assessed for each role are listed below: 

Question Types to Assess Data Engineering Skills

Few of the most common ways to assess Data Engineering Skills are as below:

• Hands-on Tasks (Recommended)
• Multiple Choice Questions

Real-world or Hands-on tasks and questions require candidates to dive deeper and actually demonstrate their skill proficiency. Using the hands-on questions in our library, candidates can be measured on practical demonstrations and multiple solution paths. For example, Apache Spark-based questions in the HackerRank library assess the ability to perform in-memory transformations using lambdas, converting RDDs to Data Frames, using broadcast variables and accumulators, writing spark jobs to perform data manipulation tasks, and so on. 

Few examples of Apache Spark hands-on project questions in our library are as below.

Examples of Apache Spark Questions

Similarly, Apache Kafka hands-on tasks test the understanding of Apache Kafka architecture, Kafka clusters, Kafka messaging systems, understanding Apache Kafka partitions and brokers, and Kafka producers and consumers, among others. Tasks include Web Analytics, Serialization, Deserialization, CDR, and so on. 

Few examples of Apache Kafka Java hands-on project questions in our library are as below.

Examples of Apache Kafka Questions

Multiple Choice Questions [MCQs], in general, assess conceptual knowledge and understanding of a skill. For example, Hadoop Multiple Choice Questions, used in the Data Engineering assessments on HackerRank, test knowledge of control flow of a map-side join, MapReduce combiners, commonly used Hadoop commands, among others. Hadoop hands-on project questions, test application-oriented skills such as analysis, performing computing operations, implementation of key functionalities in a Hadoop application, and so on.

Few examples of Hadoop multiple-choice and hands-on project questions in our library are as below.

Examples of Hadoop Questions

Customers can leverage whiteboard solutions on HackerRank Interviews as well as diagram questions for system design assessment, and so on. These questions provide insights into the candidate's thought process.

Note: Validated by our HackerRank's Skills Advisory Council, we also provide the HackerRank Skills Directory which clearly defines the competencies that can be leveraged while assessing candidates for the Data Engineering role. Please see the key competencies for the Skills listed above, on our Skills Directory here.