Overview
This article describes about the HackerRank enabled capabilities to assess the candidate's Data Engineering skills. Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more beneficial to the enterprise. At HackerRank, the Data Engineering skills can be assessed through pre-designed and custom-built tests that come with essential skills such as SQL, Apache Kafka, Hadoop, Couchbase, Apache Spark, Java, Scala, and so on.
Note: Validated by the HackerRank's Skills Advisory Council, HackerRank provides the HackerRank Skills Directory, which clearly defines the competencies that can be leveraged to assess candidates for the Data Engineering role.
Using the HackerRank's Data Engineer Role, both theoretical and practical knowledge of the associated skills can be tested. Data Engineering assessment is classified into three roles:
- Data Engineer (JavaSpark)
- Data Engineer (PySpark)
- Data Engineer (ScalaSpark)
Skills assessed for each role are listed below:
|
Role |
Skills Assessed |
|
Data Engineer (Java Spark) |
SQL (Intermediate), Java (Basic), Apache Spark (Basic), Hadoop (Basic), Kafka (Basic), Couchbase (Basic) |
|
Data Engineer (PySpark) |
SQL (Intermediate), Python (Basic), Apache Spark (Basic), Hadoop (Basic), Kafka (Basic), Couchbase (Basic) |
|
Data Engineer (Scala Spark) |
SQL (Intermediate), Apache Spark (Basic), Hadoop (Basic), Kafka (Basic), Couchbase (Basic) |
Question Types to Assess Data Engineering Skills
A few of the most common ways to assess Data Engineering Skills are:
- Hands-on Tasks (Recommended)
- Multiple Choice Questions
Real-world or Hands-on tasks and questions require candidates to dive deeper and demonstrate their skill proficiency. Using the hands-on questions in the HackerRank library, candidates can be assessed 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.
A 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, and so on. Tasks include Web Analytics, Serialization, Deserialization, CDR, and so on.
A few examples of Apache Kafka Java hands-on project questions in the HackerRank library are as below.
Examples of Apache Kafka Questions
The Multiple Choice Questions [MCQs] assess conceptual knowledge and understanding of a skill. For example, Hadoop MCQs that are used in the Data Engineering assessments on HackerRank, test the knowledge of control flow of a map-side join, MapReduce combiners, and commonly used Hadoop commands, Hadoop hands-on project questions, test application-oriented skills such as analysis, performing computing operations, implementing key functionalities in a Hadoop application, and so on.
A few examples of Hadoop multiple-choice and hands-on project questions in our library are:
Examples of Hadoop Questions