Snowflake is attaining momentum as the best cloud data warehouse solution because of its innovative features like separation of computing and storage, data sharing, and data cleaning. It gives support for popular programming languages like Java, Go, .Net, Python, etc. Tech giants like Adobe systems, AWS, Informatica, Logitech, Looker are using the Snowflake platform to build data-intensive applications.  Therefore, there is always a demand for Snowflake professionals. According to, the average salary for a Snowflake Data Architect in the US is around $179k per annum. If that is the career move you are making, and you are preparing for a Snowflake data architect job interview, the below Snowflake interview questions and answers will help you prepare.

Snowflake Interview Questions and Answers

Q1) What is a Snowflake cloud data warehouse?

Ans. Snowflake is an analytic data warehouse implemented as a SaaS service. It is built on a new SQL database engine with a unique architecture built for the cloud. This cloud-based data warehouse solution was first available on AWS as software to load and analyze massive volumes of data. The most remarkable feature of Snowflake is its ability to spin up any number of virtual warehouses, which means the user can operate an unlimited number of independent workloads against the same data without any risk of contention. Do you want to learn more - then visit Snowflake Cloud Data Warehouse Tutorial

Do you want to enhance your skills and build your career in this domain? Then enroll in " Snowflake Certification Training " this course will help you to achieve excellence in this domain.

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Q2) Is Snowflake an ETL tool?

Ans. Yes, Snowflake is an ETL tool. It’s a three-step process, which includes:

  • Extracts data from the source and creates data files. Data files support multiple data formats like JSON, CSV, XML, and more.
  • Loads data to an internal or external stage. Data can be staged in an internal, Microsoft Azure blob, Amazon S3 bucket, or Snowflake managed location.
  • Data is copied into a Snowflake database table using the COPY INTO command. 

Q3) How is data stored in Snowflake?

Ans. Snowflakes store the data in multiple micro partitions which are internally optimized and compressed. The data is stored in a columnar format in the cloud storage of Snowflake. The data objects stored by Snowflake cannot be accessed or visible to the users. By running SQL query operations on Snowflake, you can access them.

Q4) What type of database is Snowflake?

Ans. Snowflake is built entirely on a SQL database. It’s a columnar-stored relational database that works well with Excel, Tableau, and many other tools. Snowflake contains its query tool, supports multi-statement transactions, role-based security, etc., which are expected in a SQL database.

Q5) Can AWS glue connect to Snowflake?

Ans. Definitely. AWS glue presents a comprehensive managed environment that easily connects with Snowflake as a data warehouse service. These two solutions collectively enable you to handle data ingestion and transformation with more ease and flexibility.

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Q6) Explain Snowflake editions.

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Ans. Snowflake offers multiple editions depending on your usage requirements.

  • Standard edition - Its introductory level offering provides unlimited access to Snowflake’s standard features.
  • Enterprise edition - Along with Standard edition features and services, offers additional features required for large-scale enterprises.
  • Business-critical edition - Also, called Enterprise for Sensitive Data (ESD). It offers high-level data protection for sensitive data to organization needs.
  • Virtual Private Snowflake (VPS) - Provides high-level security for organizations dealing with financial activities.

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Q7) Define the Snowflake Cluster.

Ans. In Snowflake, data partitioning is called clustering, which specifies cluster keys on the table. The method by which you manage clustered data in a table is called re-clustering.

Q8) Explain Snowflake architecture

Ans. Snowflake is built on an AWS cloud data warehouse and is truly Saas offering. There is no software, hardware, ongoing maintenance, tuning, etc. needed to work with Snowflake.

Three main layers make the Snowflake architecture - database storage, query processing, and cloud services.

  • Data storage - In Snowflake, the stored data is reorganized into its internal optimized, columnar, and optimized format. 
  • Query processing - Virtual warehouses process the queries in Snowflake.
  • Cloud services - This layer coordinates and handles all activities across the Snowflake. It provides the best results for Authentication, Metadata management, Infrastructure management, Access control, and Query parsing.

Read more at - Architecture of Snowflake Cloud Data Warehouse

Q9) What are the features of Snowflake? 

Ans. Unique features of the Snowflake data warehouse are listed below:

  • Database and Object Closing
  • Support for XML
  • External tables
  • Hive metastore integration
  • Supports geospatial data
  • Security and data protection
  • Data sharing
  • Search optimization service
  • Table streams on external tables and shared tables
  • Result Caching

Related Article - [Snowflake vs BigQuery]

Q10) Tell me something about Snowflake AWS?

Ans. For managing today’s data analytics, companies rely on a data platform that offers rapid deployment, compelling performance, and on-demand scalability. Snowflake on the AWS platform serves as a SQL data warehouse, which makes modern data warehousing effective, manageable, and accessible to all data users. It enables the data-driven enterprise with secure data sharing, elasticity, and per-second pricing.

Q11) Describe Snowflake computing. 

Ans. Snowflake cloud data warehouse platform provides instant, secure, and governed access to the entire data network and a core architecture to enable various types of data workloads, including a single platform for developing modern data applications.  

Q12) What is the schema in Snowflake?

Ans. Schemas and databases used for organizing data stored in the Snowflake. A schema is a logical grouping of database objects such as tables, views, etc. The benefits of using Snowflake schemas are it provides structured data and uses small disk space.

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Q13) What kind of SQL does Snowflake use?

Ans. Snowflake supports the most common standardized version of SQL, i.e., ANSI for powerful relational database querying.

Q14) What are the cloud platforms currently supported by Snowflake?


Q15) What ETL tools do you use with Snowflake?

Ans. Following are the best ETL tools for Snowflake

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

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