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Apache Spark for Data Engineers test

Summary of the Apache Spark for Data Engineers test

This Apache Spark for Data Engineers test evaluates a candidate’s ability to use Apache Spark for large-scale data processing. This hiring test will help you hire data engineers who have practical experience using the Spark framework.

Covered skills

  • Apache Spark fundamentals

  • Data transformation and processing

  • Spark Core

  • Spark Streaming/GraphX

Use the Apache Spark for Data Engineers test to hire

Data engineers

Type

Programming skills

Time

10 min

Languages

English

Level

Intermediate
graphic image for programming skills test

About the Apache Spark for Data Engineers test

In today’s era of big data, businesses need powerful tools to process and transform it, and Apache Spark is one of the most powerful tools available today for big data operations. Since its release in 2009, its use has exponentially ramped up among companies that work with some of the largest datasets. Though one of Spark’s key advantages is its ease of use, it takes an experienced data engineer to make the best use of all of its features. When you hire data engineers already well-versed in Apache Spark, your data projects will be completed more quickly, allowing your business to focus on implementing the solutions that the data implies.

This Apache Spark for Data Engineers test evaluates candidates’ abilities to apply their understanding of Apache Spark fundamentals, use Apache Spark for data transformation and processing, use Spark Core, and use Spark Streaming/Graph X.

This screening test will help you identify data engineers and other professionals who have strong experience with the Spark framework. Candidates who do well on this test will be able to efficiently problem-solve and execute on common Apache Spark scenarios they are likely to encounter on the job.

photo of the subject matter expert for this test, Hamza A.

The test is made by a subject-matter expert

Hamza A.

A Spark data engineer with years of experience in the data field, Hamza has worked on a wide variety of machine learning, data engineering, and web scraping projects, both big and small.

With his deep interest in and devotion to the data field, he has mastered the Spark framework and other ETL frameworks, including Apache Airflow. He is continuously striving to master graph data science.

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Review from G2

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