Top 11 Snowflake Interview Questions + Guide (Updated in 2025)

Snowflake is a company that focuses on enterprise-grade, reliable software, advanced database technologies, cloud infrastructure (particularly AWS), SaaS, multi-tenant systems, and advanced data processing solutions. Furthermore, the company continues to learn and contribute to the robust, highly scalable, and reliable data processing platform.

As part of this exciting journey, Snowflake is looking for skilled and visionary individuals committed to pushing the pace of innovation, challenging conventional thinking, and driving the company’s growth. Here’s how their interview process works, highlighting expert tips and strategies on acing the Snowflake interview questions.

The interview process at Snowflake for engineering roles is designed to evaluate a candidate’s technical skills, problem-solving abilities, and fit for the company culture.

Here’s an outline of the process.

1. Preliminary Screening: If a candidate’s skills match an open position, a recruiter or hiring manager will reach out for a preliminary screening, which could include a phone screen.
2. Online Assessment or Coding Challenge: After the initial screening, candidates might be required to complete an online assessment or coding challenge, which could be quite challenging and may contain LeetCode-style questions or domain-specific tasks.
3. Technical Interviews: This phase includes technical interviews to evaluate the candidate’s knowledge in their respective domains. The exact format and number of interviews can vary, but it generally includes phone screens, and possibly additional technical interviews or panel discussions.
4. Onsite/Video Interviews: Candidates who perform well in the earlier stages are invited for onsite or video interviews. During these interviews, candidates could face a mix of technical and behavioral questions. The exact format may vary depending on the team and role, with possibly additional steps during this stage of the process.
5. Offer and Onboarding: Post-interview, there’s a decision-making phase to determine whether there’s a mutual fit. If successful, an offer is extended, and the onboarding process begins.

The entire recruitment process for engineering roles at Snowflake can take between two to four weeks and might require at least one in-person interview at one of Snowflake’s office locations. It’s also worth noting that additional steps may be included in the interview process depending on the specific role or team the candidate is applying for.

Snowflake’s powerful data warehousing technology provides an environment where SQL (Structured Query Language) plays a pivotal role in querying and managing large datasets. Being proficient in SQL is crucial for candidates aiming to secure technical roles at Snowflake, as it forms the backbone of data retrieval, manipulation, and analytics within the Snowflake platform.

Here are a few practice questions to hone your SQL skills:

1. Create an SQL query to sample every 4th row from a transactions table, ordered by date.

Given a transactions table with date timestamps, write an SQL query to sample every 4th row ordered by the date.

2. Create a query to show the number of users, transactions, and total order amount per month in 2020.

Write a query to show the number of users, number of transactions placed, and total order amount per month in the year 2020. Assume that we are only interested in the monthly reports for a single year (January-December).

3. Write a SQL query to create a histogram of comments per user for January 2020.

Given a users table and a comments table, write an SQL query to create a histogram showing the number of comments per user for the month of January 2020. Comments created outside of this month should be counted in a “0” bucket.

4. Given a table exam_scores, form a new table to track the scores for each student.

To finish a class, students must pass four exams (exam IDs: 1,2,3, and 4).

Create a new table to track the scores for each student using data from the exam_scores table, which contains information about all the exams students took. Note that the students took each exam only once.

5. Find a user that has the highest average number of unique item categories per order.

You have been provided with two tables: user_orders and ordered_items. A user can have multiple orders, and within each order, there may be multiple items with either the same or different categories.

Note that you may assume that there is only one user with the highest average number of unique item categories per order.

For practicing SQL interview questions, consider using the SQL learning path or the full list of SQL questions in our database.

Given Snowflake’s emphasis on cloud-based data solutions and advanced data processing, having a strong foundation in coding and algorithms is essential. It allows for efficient problem-solving and the development of robust, scalable software essential for handling complex data operations.

Below are some practice questions to prepare for the coding and algorithm aspect of Snowflake interviews:

6. Write a function to determine if there exists a one-to-one correspondence between the characters of two strings.

Given two strings, string1 and string2, write a function str_map to determine if there exists a one-to-one correspondence (bijection) between the characters of string1 and string2. For the two strings, our correspondence must be between characters in the same position/index.

7. Design three classes: text_editor, moving_text_editor, and smart_text_editor with specific functionalities.

You have been tasked with designing three classes: text_editor, moving_text_editor, and smart_text_editor. These classes are to be created with specific functionalities as defined below.

8. Write a function that returns the indices of two integers in an array that add up to a target integer.

Given an array and a target integer, write a function sum_pair_indices that returns the indices of two integers in the array that add up to the target integer. If not found, just return an empty list.

Snowflake’s architecture and services are conducive to machine learning applications, with capabilities to handle vast datasets efficiently. The platform facilitates ML engineers and data scientists in developing, training, and deploying machine learning models.

Understanding machine learning principles, and algorithms, and how they can be applied to solve real-world problems is crucial for candidates eyeing roles in this domain at Snowflake.

Below are some questions to gauge your understanding of machine-learning concepts:

9. What metrics would you use to track the accuracy and validity of a spam classifier model?

Assume you’ve built a V1 of a spam classifier for emails. What metrics would you use to evaluate the model’s accuracy and validity?

10. How would you build a model to bid on unseen keywords given a dataset of keywords and their prices?

You’re working on keyword bidding optimization and have a dataset with two columns: one for keywords being bid against and another for the price paid for those keywords. How would you construct a model to bid on a new, unseen keyword?

11. How would you build a model to detect fraudulent transactions and notify customers via text message?

You work at a bank that wants to create a model to identify fraud on its platform. The bank also wants to implement a text messaging service that alerts customers when the model detects a fraudulent transaction, allowing the customer to approve or deny the transaction via text. How would you build this model?