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Google Cloud BigQuery Skills Assessment Test
Test duration:
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Level of experience:
Entry Level/Mid/Senior

Google Cloud BigQuery Skills Assessment Test

This skill test helps evaluate and measure various skills, including Java, Python, Google Cloud API scripting, and more, that are relevant to the job profile. Our test also helps Talent Acquisition professionals reduce recruitment timelines by up to 45% and aids L&D managers in re-skill employees within half the time needed earlier.

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What is Google Cloud BigQuery?

It is a highly scalable, serverless data warehouse with an integrated query engine. This highly efficient engine allows the processing of terabytes of data in seconds and petabytes in only a few minutes. It maximizes flexibility by isolating the computer engine that analyses data from your storage options.

Why Choose iMocha?

Our customizable test offers features that simplify your evaluation of employees and candidates for Data Engineers/Developers, Cloud architects, and other job roles. You can utilize its advanced features such as AI-LogicBox, Coding Simulator, Code replay, and other features to assess an individual's tech skills accurately. Its detailed analytical report further assists you in making data-backed hiring and upskilling decisions free from unconscious bias.

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How it works

Test Summary

This skill assessment test assesses individuals who possess the following skills;

  • Understanding of BigQuery features and architecture
  • Knowledge of data modeling principles and methods
  • Ability to load data from a variety of sources
  • Proficiency with SQL and other tools for data querying
  • Knowledge of performance optimization strategies to increase the speed and effectiveness of queries
  • Expertise in Big Query's security and access control techniques
  • Understanding of Big Query's pricing and payment structures
  • Awareness of integrations with other Google Cloud services

Our test is built by SMEs (Subject Matter Experts) to effectively analyze theoretical knowledge and practical abilities relevant to the domain's skills.

Useful for hiring
  • Data Engineer
  • Data Analyst
  • Business Intelligence Analyst
  • Data Scientist
  • Database Administrator
  • Cloud Architect
  • Solutions Architect
  • Software Engineer (with a focus on data or cloud technologies)
  • Analytics Manager
  • Big Data Engineer
Test Duration
No. of Questions
Level of Expertise
Entry Level/Mid/Senior
Topics Covered





Sample Question
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Topics covered


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You can customize this test by

Setting the difficulty level of the test

Choose easy, medium, or tricky questions from our skill libraries to assess candidates of different experience levels.

Combining multiple skills into one test

Add multiple skills in a single test to create an effective assessment and assess multiple skills together.

Adding your own
questions to the test

Add, edit, or bulk upload your coding, MCQ, and whiteboard questions.

Requesting a tailor-made test

Receive a tailored assessment created by our subject matter experts to ensure adequate screening.
How is the Google Cloud BigQuery skills test customized?
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This test can be customized in several ways. Our customization suite offers you the choice between an automated or manual selection of questions and the flexibility to tweak them based on the seniority, proficiency, and competency level of the desired job profile. You also get the freedom to assess an individual's knowledge of different BigQuery skills, including data modeling, querying, performance optimization, and more.

What are the most common interview questions related to Google Cloud BigQuery?
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Some frequently asked interview questions include the following:

  • What is GCP App Engine?
  • Can you explain what makes legacy SQL different from standard SQL?
  • Is BigQuery structured or unstructured?
  • What are the products supported by GCP?
  • How can we load data from Cloud Storage?
  • Explain the Technical Architecture of Google BigQuery
What are the required skillsets to work on Google Cloud BigQuery?
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Technical skills include:

  • Knowledge of data warehousing principles.
  • Strategies for speed optimization and SQL queries.
  • Understanding database architecture, data modeling, and cloud computing is advantageous
  • Familiarity with other Google Cloud services and technologies, such as Apache Beam, Cloud Dataflow, and Cloud Storage

Non-Technical Skills:

  • Analytical Skills
  • Problem-Solving skills
  • Effective Communication
  • Project management
  • Adaptability