Big Data Engineering Skill Test

Skill summary

The big data engineering skill test evaluates your expertise in designing, developing, implementing, and managing large-scale data processing systems, storage systems, and infrastructure to support big data initiatives. 

A strong knowledge of big data technologies, platforms, distributed computing, data integration, and ETL processes, as well as strong analytical and problem-solving skills, will help you pursue careers in big data engineering.


Multiple Choice Questions


10 min






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Why we created this test

This test evaluates candidates’ proficiency in critical areas such as data processing and analysis, data modeling and database design, data architecture, and system design.

Candidates who do well on the big data engineering skill test have good expertise in Hadoop, Spark, Java, Python, cloud computing platforms, and tools.

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Big Data Engineering Glider AI skill intelligence platform
Big Data Engineering Glider AI skill intelligence platform

Skills evaluated

Big data engineers need to have certain competencies to do their job well. The skills that they should have are:
Frameworks like Apache Pig, Flume, MapReduce, HDFS, YARN
Talend, IBM Data Stage, Pentaho, Informatica
Analytical skills and Data visualization
Hadoop ecosystem
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Related roles

Use the big data engineering skill test to hire for these roles:
Data Architect
Data Security Analyst
Database Manager
Business Intelligence Analyst
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Big Data Engineering Glider AI skill intelligence platform

Science-backed questions for hundreds of roles

Use these sample questions to evaluate skill and fit for the big data engineer role before hiring.

1. The Apache Spark project is characterized as ________________
  • Large scale graph processing 
  • Large scale machine learning 
  • Live data stream processing 
  • All of these 
  • None of these 
2. Where is Big SQ not applied in terms of performance improvement?
  • Query Optimization 
  •  None of these 
  •  Predicate Push down 
  •  Compression efficiency 
  •  Load data into DB2 and return the data 
3. What does SerDe interface not provide?
  • Deserializer interface takes a string or binary representation of a record, and translates it into a Java object that Big SQL can manipulate 
  •  None of these 
  •  Allows SQL-style queries across data that is often not appropriate for a relational database 
  •  SerDe interface has to be built using C or C++ language 
  •  Serializer takes a Java object that Big SQL has been working with, and turns it into a format that BigSQL can write to HDFS 
4. What will be the outcome of Bulk Load application in HBase for loading large data volumes?
  • There will be no change in the outcome 
  • Less network resource but increased CPU usage 
  • Less CPU usage but increased network resource 
  • All of these 
  • None of these 
5. How do you improve query performance on large Hive tables?
  • De-normalizing data 
  •  Indexing 
  • Bucketing 
  • Partitioning 
  • None of these 

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