Snowflake Interview Questions

Boost your Career with Snowflake. Snowflake is one of the ultimate cloud data warehouse solutions with innovative capabilities like data sharing, data cleansing, compute and storage isolation. It supports programming languages like .Net, Java, Python and Go language.

Selecting the right career opportunity in the right organization is one of the critical steps you have to take in this competitive IT world. So to help you in your preparation for the advancement of your career, HKR is providing you with the most frequently asked Snowflake interview questions. In this blog, we have divided the frequently asked interview questions into three levels: Basic level, Intermediate level and Experienced level. Let's start with our basic level interview questions. 

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Snowflake Interview Questions and Answers for Experienced,Freshers & Intermediate.

Basic snowflake interview questions:

1. What is Snowflake?

It is a cloud data-based warehouse that is used as a software as a service. It is made up of unique architecture for dealing with multiple aspects of data and analysis. Snowflake differs from any other traditional data warehouse solutions with advanced features such as simplicity, improved performance, high concurrency and profitability. The shared data architecture of Snowflake physically separates calculation and storage, which traditional offerings do not allow. It simplifies the process by allowing companies to store and analyze huge amounts of data with cloud tools. Snowflake transformed the data warehousing industry by allowing all data to be consolidated into one centralized system.

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2. What is special about snowflake architecture?

Snowflake has a unique and advanced architecture. It is a mixture of shared-nothing and shared-disk architectures. It utilizes a central data repository for storing data in a consistent manner and makes it accessible from all the computing nodes of the platform. Like the shared-nothing architecture, Snowflake uses massively parallel processing computed clusters to run queries. With shared-disk architecture, data management is simplified. It provides improved performance and scalability.

Snowflake architecture is made up of three layers: 

Query processing: In this layer, the virtual warehouses processes the queries. 

Data Storage: Here, the data is arranged in columnar, internal optimized format.  

Cloud Services: It is responsible for the coordination and management of all the associated activities in snowflake. It is also responsible for and delivers the best results when it comes to metadata management, infrastructure management, authentication, query analysis, and access control.

3. How to access Snowflake's data warehouse?

The usual ways to access Snowflake's data warehouse are: 

  • ODBC Drivers
  • JDBC Drivers
  • Python Libraries
  • Web User Interface
  • SnowSQL Command-line Client 
4. What benefits does a Snowflake database offer?

Snowflake is natively designed for the cloud and deals with a number of problems that are not solved by conventional warehouse systems. Here are our top 5 benefits from using the Snowflake data platform:

  • High security
  • High availability
  • Seamless data sharing
  • High-speed performance
  • Concurrency and accessible
  • Handles both structured and unstructured data
5. How is the data securely stored in Snowflake?

Data security is a top priority of every organization. Snowflake meets the industry's highest safety standards for encrypting and securing data stored and customer accounts in Snowflake. It provides the best key management features without additional charge.

The following are the security measures that Snowflake uses to protect client data:

  • Snowflake utilizes a managed key for automatically encrypting the data it contains.
  • Snowflake relies on TLS for protecting communication between customers and servers.
  • It enables you to choose a geographic location for storing your data depending on your cloud region.
6. How does Snowflake Data Compression work?

By default, all the data is compressed in Snowflake. Snowflake selects the top compression algorithms and cannot be configured by end-users. The best thing about Snowflake is that after compressing the data, Snowflake charges the customer according to the final size of the compressed data. 

Benefits of data compression in snowflake:

  • Storage costs are lower compared to native cloud storage costs due to compression.
  • There is no storage cost for disk caches.
  • Storage overheads close to zero when cloning or sharing data. 

7. What is Snowflake Catching?

Snowflake stores the data cache in the SSD along with the result cache to enhance the performance of SQL queries. It captures the result of each query that you execute, and each time a new query is submitted. It will check it with the previously executed queries to find out a match. If any related query is available, it utilizes a cached result set rather than running the query. It reduces the amount of time spent on queries and retrieves the results directly from the cache.

Various kinds of caching in Snowflake:

  • Virtual-Warehouse Local-Disk Caching
  • Query Results Caching
  • Metadata Cache 

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8. What is Time Travel?

The Snowflake Time Travel tool provides us with access to past data at any time during the specified period. This enables us to see which data we can edit or delete. This tool is used to accomplish the following tasks:

  • Restore objects associated with data which may have unintentionally been lost.
  • To examine data usage and data changes within a given time period.
  • Duplication and backup of data from the most important points of history.
9. What is Fail-safe?

It is an advanced functionality available in Snowflake for ensuring data security. It is an essential part of the snowflake data protection lifecycle. It even offers additional seven days of storage even after the completion of the travel period.

10. Explain Snowflake features.

Some of Snowflake's outstanding features include:

  • Cloud Services
  • Compute layer
  • Database Storage
  • Easy data sharing
  • Availability and Security
  • High-speed performance  
  • Supports unstructured and structured data
  • Concurrency and Accessibility

Intermediate level Snowflake interview questions:

11. What are the different editions of Snowflake?

Snowflake has various editions which will assist the clients according to needs. Snowflake Editions are as follows:

Standard Edition: This edition is perfect for beginners and is called the Introductory Level offering of Snowflake. It offers users limitless access to standard features.

Enterprise Edition: It comes with standard editing features and services and includes some of the extra f features needed for large Enterprises. 

Business-critical edition: It is also referred to as an enterprise for sensitive data. business-critical edition offers high-level data protection support to protect sensitive data for meeting the needs of the organization.

Virtual Private Snowflake: It is responsible for providing a high level of security for organizations that handle financial activities.

12. What is the virtual warehouse?

A virtual warehouse is one or more clusters that approve users for carrying out operations such as data loading, queries, and other DML operations. Virtual warehouses endorse users with the required resources such as CPU, temporary storage to perform various snowflake operations. 

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13. Why do we use Fail-safe?

To reduce the risk factor, DBA typically performs complete and incremental data backups on a regular basis. This process consumes more storage space and can sometimes be double or triple. In addition, the process of recovering data is expensive, takes time, requires a company downtime, and even more.    

14. What are the data shares in Snowflake?

The snowflake data sharing option enables users to share data objects safely in a database of your account with other snowflake accounts. All database objects shared among snowflake accounts are readable and cannot be modified. Database objects that are shareable in Snowflake are external tables,  secure views, tables, Secure materialized views and Secure UDFs.

There are three kinds of data sharing:

  • Sharing data between management units
  • Sharing Data between functional units
  • Data sharing between geographically dispersed area 

15. What is Zero-copy cloning?

It is an implementation that enables us to create a copy of tables, schemas and databases without actually copying the data. For performing zero-copy in Snowflake, we must use a keyword named CLONE. This option allows you to obtain real-time data from production and carry out several actions. 

Related Article: Snowflake Vs Redshift

16. What is Snowpipe?

Snowpipe is a constant and cost-effective service which we use to load the data into Snowflake. Systematically Snowpipe loads the file data as soon as it is feasible on the stage. Snowpipe makes the data loading process easier by loading the data into micro-batches and shaping the data to be analyzed. Some of the advantages of Snowpipe are: 

  • Cost-effective
  • User friendly
  • Resilience
  • Live insights

17. What is Horizontal scaling and Vertical Scaling?

Horizontal scaling enhances concurrency. When we need to support extra users, then we can increase the number of Virtual warehouses using auto-scaling to support and deal with more user requests instantly.

Vertical Scaling reduces processing times. When we have enormous workloads and want to optimize them and get them working faster, we can think about choosing a larger virtual warehouse size.

18. Explain about the database storage layer.

Each time the data is loaded into Snowflake, it organizes the data in a compressed, optimized, and columnar format. Following this process, the data is optimised and stored in the cloud. Following this process, the data is optimised and stored in the cloud. Snowflake is responsible for the way data is stored, including data organization, structure, compression, file size, metadata, statistics and many other aspects related to data storage. Any data objects stored in Snowflake are hidden and not accessible. Data objects can only be accessed by carrying out SQL query operations.

19. What is the Query processing layer?

All the queries are executed on this processing layer. Snowflake utilizes "virtual warehouses for processing queries. Every virtual warehouse is a Massively Parallel Processing computing cluster consisting of several nodes assigned by snowflake’s cloud provider. In the query processing layer, every Virtual warehouse will not share its computational resources with other virtual warehouses. Each virtual warehouse is thus independent and does not have an impact on the other virtual warehouses in the event of a failover. 

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20. What is the Cloud Service layer?

The Cloud Services layer is a collection of services which will coordinate several tasks on the Snowflake platform. All these services are linked and work with good coordination to deal with user requests, from sign in to query dispatch. This layer carries out the calculation of instances assigned by Snowflake’s cloud manager. The various services administered under this layer include:

  • Access control
  • Authentication
  • Metadata management
  • Infrastructure management
  • Optimization and query parsing

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 Snowflake interview questions for Experienced:

21. What is Materialized view?

A materialized view is a pre-computed dataset that is derived from query specification. Since the data is pre-computed, it becomes much easier to query the materialized view compared to a non-materialized view from the base table of the view. In plain language, materialized views are designed to improve the query performance of common and repetitive query models. Materialized views are the main database objects and accelerate projection, selection operations and expensive aggregation for queries that execute on larger datasets. 

22. What is Schema?

Schemas and databases used for the arrangement of the stored data. It is a logical grouping of database objects like views, tables, etc. The advantages of Snowflake diagrams are that they provide structured data and use limited disk space. 

23. What ETL tools are you using in Snowflake?

Some of the best ETL tools of  Snowflake's are:

  • Etleap
  • Blendo
  • Matillion
  • Hevo Data
  • StreamSets
  • Apache Airflow

24. What programming languages are supported in Snowflake?

Snowflake supports various programming languages such as Go, C, . NET, Java, Python, Node.js, etc.

Related Article: Snowflake Vs BigQuery

25. What is a clustering key in Snowflake?

It is a subset of columns in a table which helps us to co-locate the data inside the table. It is best suited to situations in which tables are extended; the sequence was not perfect because of DML.

26. What is a Stage?

The Stage acts like the central area we use to upload the files. Snowpipe discovers the files when they reach the staging area and loads them systematically into the snowflake.

Stages supported by snowflake are as follows:

  • User Stage
  • Table Stage
  • Internal Named Stage

27. Is Snowflake OLAP or OLTP?

Snowflake is developed as an OLAP(Online Analytical Processing) database system. Depending on the use, we may also use it as online transaction processing (OLTP). 

28. How can we execute Snowflake Procedure?

Stored procedures enable us to create modular code that includes complex business logic by adding different SQL statements with procedure logic. Following are the steps to execute the Snowflake procedure:

  • Execute the SQL statement
  • Retrieve the results of the query.
  • Retrieve the result set metadata.

29. Does Snowflake maintain stored procedures?

Yes, Snowflake will maintain stored procedures. The stored procedure is identical to a function, which is created one time and used more than once. With the CREATE PROCEDURE command, it may be created and with the "CALL" command, it may be executed. Stored procedures are built into the Javascript API. These APIs allow stored procedures to carry out database operations such as UPDATE, SELECT and CREATE. 

30. What is a Columnar database?

The columnar database as opposed to traditional databases. It stores data in columns instead of rows, facilitates the analytical query processing method, and provides more incredible database performance. The Columnar database makes the analysis process easier and represents the future of business intelligence.

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 All the above are some of the frequently asked interview questions in the topmost companies. We trust this Frequently Asked Questions has been helpful to you. We are attempting to include more frequently asked questions that will help you get ready for your interview. Keep an eye out for HKR Trainings blogs for more questions.

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Research Analyst
As a Senior Writer for HKR Trainings, Sai Manikanth has a great understanding of today’s data-driven environment, which includes key aspects such as Business Intelligence and data management. He manages the task of creating great content in the areas of Digital Marketing, Content Management, Project Management & Methodologies, Product Lifecycle Management Tools. Connect with him on LinkedIn and Twitter.