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Top 20 GCP Interview Questions: A Guide for All Skill Levels

Approach your GCP interview with confidence. Leverage expert tips and access practical interview questions and answers.
Jun 2024  · 13 min read

Most job descriptions in today’s job market list cloud skills in the “Required” section or, at the very least, in the “Nice-to-have” section just below. This trend is not role-specific. Whether you are developing applications, working with data, or specializing in security, employers need you to utilize their chosen cloud provider.

In the last 5 years, I've worked in many startups, and, cliché as it sounds, I've worn many hats. I have been hands-on with Google Cloud Platform (GCP) and I have also conducted 40+ technical interviews where I tested fellow engineers’ knowledge on the topic.

This guide offers my top advice for tackling GCP interview questions tailored to your skill level and role. You are welcome to jump through to the section that feels most relevant to you. However, the general sections serve as building blocks for role-specific ones, so I would recommend reading these first.

And before you start: If you are completely new to cloud computing, I recommend taking our Introduction to Cloud Computing course first. This course breaks down cloud basics, explains key terms like scalability and latency, and covers the advantages of cloud tools from providers like Google Cloud.

Basic GCP Interview Questions

For entry-level candidates, GCP interview questions and answers have little or no technical elements. The idea is to gauge your understanding of GCP’s offerings and how the products fit together. You will most likely encounter these questions if you have never worked with GCP, or if the interviewer isn’t certain of your skill level and wants to start with the basics.

What you need to know

You should be familiar with core GCP services, like Compute Engine, Kubernetes Engine, Cloud Storage, BigQuery, Cloud SQL, and Pub/Sub. There might also be questions on:

  • Identity and Access Management (IAM): Understanding IAM roles, permissions, and how to manage user access within GCP.
  • Data Storage and Databases: Knowledge of Cloud Storage, Cloud SQL, Cloud Spanner, Firestore, and Bigtable, including their use cases and configurations.
  • Serverless Computing: Familiarity with Cloud Functions, Cloud Run, and App Engine, and how to deploy and manage serverless applications.
  • Monitoring and Logging: Proficiency with Google Cloud's Operations Suite (formerly Stackdriver), including Monitoring, Logging, Trace, Debugger, and Error Reporting to ensure system reliability and performance.

If these concepts sound unfamiliar and you don’t know where to start, try our Introduction to GCP course. It will give you a solid foundation on the above topics.

Questions you might get

Here are some questions an interviewer might ask, with sample answers provided:

1. What is Google Compute Engine, and what are its primary use cases?

4. What is a BigQuery and how does it handle large datasets?

Intermediate GCP Interview Questions

These questions will come once your interviewer has established that you have some basic knowledge of GCP's offerings. They are usually a bit more technical and will test your understanding of specific services, their configurations, and how to use them effectively in various scenarios. 

You will likely be able to answer them if you have hands-on experience with GCP and have previously managed resources, implemented IAM policies, configured VMs, or if you have completed our Understanding Cloud Computing course.

What you need to know

You need to build on your knowledge of GCP’s offerings and showcase a deeper understanding of the following services:

  • Compute and Scaling Solutions: You should have a thorough understanding of Compute Engine, Kubernetes Engine, and App Engine, including concepts such as autoscaling, load balancing, and resource optimization.
  • Networking: It is essential to be familiar with Virtual Private Cloud (VPC), VPC Peering, Shared VPC, and VPNs, as well as the configuration and management of subnets, firewalls, routes, VPNs, and load balancing.
  • Database Solutions: You need to understand Cloud SQL, Cloud Spanner, Bigtable, and Firestore, including their configurations and appropriate use cases.
  • IAM: You should know advanced IAM features such as custom roles, service accounts, and workload identity federation.
  • DevOps and CI/CD Practices: Knowledge of Cloud Build, Container Registry, and CI/CD pipeline automation is important for efficient development and deployment practices.
  • Security and Compliance: You should be aware of GCP’s security offerings, including encryption methods, security key management, and adherence to compliance standards.
  • Big Data and Analytics: A good grasp of BigQuery, Data Studio, Dataprep, and Looker is necessary for large-scale data analysis and visualization tasks.

You don’t need to be an expert in all of these topics. Just being aware of the most common features and configuration options goes a long way!

Questions you might get

Here is a list of common interview questions paired with suggested answers:

5. How do you configure and manage autoscaling in Google Compute Engine?

To configure and manage autoscaling in Google Compute Engine, I would start by setting up instance groups. Then, I would define autoscaling policies based on relevant metrics such as CPU utilization and load balancing usage. This configuration ensures that the system scales up during high demand to maintain performance and scales down during low demand to optimize cost efficiency.

Lifecycle of a message through GCP Pub/Sub

Lifecycle of a message through Pub/Sub. Source: GCP Pub/Sub Documentation

Advanced GCP Interview Questions

At this level, interviewers will look for deep technical expertise, hands-on experience, and the ability to architect complex solutions in GCP. They will expect your answers to take into account best practices for optimizing and securing cloud environments. Although there may be some exceptions, you should only be asked advanced questions if you are applying for a senior position or a role with a strong DevOps component.

What you need to know

On top of the Basic and Intermediate knowledge mentioned above, your interviewer could ask you about the general architecture and design of scalable cloud solutions, and how to leverage features like multi-region deployments, load balancing, autoscaling, and disaster recovery. You should also know how to manage hybrid and multi-cloud solutions and be able to implement advanced security practices using IAM, VPC security, data encryption, and GCP’s tools for monitoring and protection.

Questions you might get

Below are potential interview questions along with example responses:

GCP Interview Questions for Data Scientist Roles

If you are applying to a data scientist role, your interviewer will want to test your ability to work with large datasets, apply statistical methods, build predictive models, and harness cloud resources for data analysis.

What you need know for Data Scientist roles

You should have a good knowledge of GCP’s core services and have an understanding of their capabilities, use cases, and integration patterns. Data Scientists will also need to know about:

  • Setting Up and Managing a Data Science Environment: This involves configuring and optimizing the environment for efficient data processing and analysis.
  • BigQuery: GCP BigQuery interview questions are very common in data scientist interviews, so make sure you are aware of the different features and performance optimization options it offers.
  • Machine Learning Tools: You should be familiar with AI Platform for training and deploying models, AutoML for creating custom models without extensive coding, TensorFlow for building and training neural networks, and BigQuery ML for performing machine learning directly within BigQuery.
  • Data Preprocessing: Understanding how to use Dataflow for scalable data processing and Dataprep for data cleaning and transformation is crucial. These tools help in preparing data for analysis and machine learning tasks efficiently.

Many of these topic are covered in our Introduction to BigQuery course, if you would like a refresher.

Questions you might be get in Data Scientist interviews

Here are sample questions and answers:

11. How do you handle data preprocessing and feature engineering in GCP?

To handle data preprocessing and feature engineering in GCP, I use Cloud Dataflow for scalable data transformation tasks and Dataprep for data cleaning. I leverage BigQuery’s SQL capabilities to perform feature engineering, such as creating new features, handling missing values, encoding categorical variables, and scaling features to ensure they are in the right format for machine learning models.

12. How do you ensure the reproducibility and scalability of your machine-learning experiments on GCP?

To ensure the reproducibility and scalability of my machine-learning experiments on GCP, I version datasets and models to keep track of changes and updates. I use AI Platform Pipelines to orchestrate ML workflows and ML Metadata for tracking metadata related to experiments. Additionally, I use Kubernetes Engine to create containerized environments, which ensures consistent and scalable runs of my experiments.

13. How do you use TensorFlow and AI Platform for deep learning projects?

To use TensorFlow and AI Platform for deep learning projects, I start by setting up a deep learning environment with TensorFlow, where I create and train neural networks. I leverage AI Platform for distributed training and hyperparameter tuning to optimize the model's performance. Once the model is trained, I deploy it using AI Platform for serving predictions. To further optimize performance and manage computational resources, I monitor resource usage and adjust the infrastructure as needed, ensuring efficient use of computational power.

GCP Interview Questions for Data Engineer Roles

Data Engineers are responsible for designing and building scalable and reliable data systems, managing data pipelines, and ensuring data quality and reliability on GCP.

What you need to know for Data Engineering Roles

You should have a good knowledge of GCP’s core services and have an understanding of their capabilities, use cases, and integration patterns. GCP Data Engineer interview questions also include the following topics:

  • Data Architecture and Modeling: You should be familiar with BigQuery, Bigtable, Firestore, Pub/Sub, schema design, and data modeling techniques. This includes understanding how to design efficient and scalable data architectures that meet specific business requirements.
  • Data Processing and Pipelines: Knowledge of Dataflow, Dataproc, Cloud Storage, and Cloud Scheduler is essential. You should understand how to use these technologies for batch and stream processing, data transformation, orchestration, and scheduling to build robust data pipelines.
  • Performance Optimization: You need to be aware of techniques for optimizing the performance and cost of data processing and storage solutions on GCP. This includes using partitioning, clustering, indexing, caching, and resource management strategies to ensure efficient and cost-effective data operations.

Questions you might get in Data Engineering interviews

Some questions and answers include:

14. How do you handle data partitioning and sharding in a distributed database system on GCP?

To handle data partitioning and sharding in a distributed database system on GCP, I would use data partitioning and sharding techniques to ensure scalability and performance. Range partitioning involves dividing data based on a range of values, while hash partitioning distributes data based on a hash function. Composite partitioning combines multiple partitioning methods. These strategies are implemented in services like Bigtable, Firestore, or Cloud Spanner to manage data efficiently and ensure quick access and retrieval.

15. How do you handle schema evolution and versioning in a data lake architecture on GCP?

To handle schema evolution and versioning in a data lake architecture on GCP, I use tools like Avro or Protobuf to manage schema changes over time. I maintain a schema registry to version schemas and ensure consistency across different data sets. Additionally, I implement data governance practices to maintain data consistency and ensure backward compatibility, making it easier to manage changes and updates without disrupting existing workflows.

16. How would you implement a data pipeline using Google Cloud Dataflow and BigQuery?

To implement a data pipeline using Google Cloud Dataflow and BigQuery, I would start by setting up Dataflow for ETL processes. This involves writing Dataflow jobs to extract data from various sources, transform it as needed, and load it into BigQuery. I would integrate Pub/Sub for real-time data ingestion, ensuring timely and accurate data processing. Additionally, I would handle data schema, apply partitioning strategies, and use optimization techniques to ensure efficient data storage and retrieval in BigQuery.

GCP Data Pipeline architecture

Source: GCP Data Pipeline Architecture Article

GCP Interview Questions for Cloud Architect Roles

Most of the questions here will test your expertise in architecting solutions that meet both business and technical requirements. Your interviewer will want to make sure that the solutions you propose are reliable, secure, and cost-effective.

What you need to know for Cloud Architect Roles

You should have a good knowledge of GCP’s core services and have a deep understanding of their capabilities, use cases, and integration patterns. 

As a cloud architect, you could be responsible for the migration or integration of entire systems to GCP. Therefore, GCP architect interview questions can test your expertise on hybrid or multi-cloud architectures, and the best practices for designing reliable cloud solutions at scale. Lean into your previous experience, and talk about use cases and scenarios that you have successfully handled in the past.

Questions you might get in Cloud Architect interviews

Some questions and answers include:

17. Can you explain the steps and considerations for migrating a large-scale on-premises application to GCP?

To migrate a large-scale on-premises application to GCP, I would start with an assessment phase to evaluate the current infrastructure and identify dependencies. In the planning phase, I would design the migration strategy, including selecting appropriate GCP services and tools like Migrate for Compute Engine for VM migration and data transfer options. During the execution phase, I would re-architect the application for the cloud, handle dependencies, perform thorough testing, and implement strategies to minimize downtime.

18. Can you describe the use cases and challenges linked to multi-cloud applications, i.e. integrating GCP with other cloud providers?

Multi-cloud applications are often used for disaster recovery, data analytics, or workload distribution. Integrating GCP with other cloud providers involves challenges such as network connectivity, data transfer, identity management, and maintaining security across environments. Tools like Anthos can help manage multi-cloud Kubernetes clusters, ensuring seamless integration and efficient operation.

19. Explain how you would handle disaster recovery and business continuity planning in a cloud architecture on GCP.

For disaster recovery and business continuity planning in a GCP cloud architecture, I would set up cross-region replication to ensure data redundancy. Implementing failover mechanisms would help maintain service availability in case of failures. Regular backups are crucial for data protection, and I would also test disaster recovery procedures periodically to ensure they are effective and up-to-date.

20. Explain how you would optimize the cost of cloud infrastructure on GCP while ensuring performance and scalability.

To optimize the cost of cloud infrastructure on GCP, I would use Compute Engine Preemptible VMs for cost-effective computing. Rightsizing instances ensures that resources are appropriately allocated based on usage. Leveraging committed use discounts can further reduce costs. Additionally, I would use cost management tools like Cost Explorer and Budgets to monitor and control spending while maintaining performance and scalability.

Note: Another topic that is often overlooked but comes up quite often in interviews is cost optimization. According to the Flexera 2024 State of the Cloud Report, companies make cost-optimization a priority when it comes to cloud computing, so make sure you know how to use cost management tools in GCP and that you understand strategies like resource provisioning and rightsizing.

Final Thoughts

Now that you have a better idea of what to expect in your GCP interview, you can start filling the gaps in your knowledge. 

While theoretical courses are great to get started, I find that hands-on practice with real-world scenarios is the best way to gain GCP expertise. There are a lot of resources out there that you can use, and I would recommend the Google Cloud Training courses if you can afford the $29 monthly subscription. 

Additionally, DataCamp's DataLab is an excellent platform for practicing your skills. DataLab is a cloud-based notebook that allows you to experiment with code, analyze data, collaborate with others, and share insights with no installation required. It provides a seamless environment to work on real-world data, making it a practical tool for honing your data skills.

You can also take your studies further and add an official GCP certification to your CV or LinkedIn profile to showcase your skills to prospective employers. For each certification, Google provides a free practice exam. Their purpose is to help you prepare for the official test, but they also work great for interviews so make sure you check them out.

I hope you found this guide helpful, and I wish you the best of luck for your interview!

Frequently Asked Questions

What should I NOT do when prepping for a GCP interview?

Try not to memorize facts only. Instead, strive to understand the underlying concepts and be prepared to discuss real-life scenarios.

Do I need to memorize GCP commands?

Not at all. This is what documentation is for!

Do I need to have hands-on experience with GCP before an interview?

It is certainly beneficial, but isn’t a strict requirement. Demonstrating a strong understanding of GCP concepts, along with a willingness to learn and adapt, can go a long way.

I have experience with AWS or Azure. How much of that knowledge is transferable?

Cloud providers have different terminology and unique services but the fundamental cloud computing concepts are the same. If you have previous experience with another cloud provider, you will be able to draw parallels between services and learn GCP quicker than if you started from scratch.

What should I do if the interviewer asks a question that I don't know the answer to?

If you don’t know the answer to a question, don’t panic! If the question is about a service you don’t know or a scenario you have never encountered before, you can ask clarifying questions. Take some time to think, explain your thought process, and lean into your experience to propose a logical answer.


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Author
Marie Fayard

Senior Software Engineer, Technical Writer and Advisor with a background in physics. Committed to helping early-stage startups reach their potential and making complex concepts accessible to everyone.

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