11 VTEX SQL Interview Questions (Updated 2024)

Updated on

June 23, 2024

VTEX employees use SQL daily for analyzing e-commerce transactions for optimization and creating customer behavior models based on product interactions. Because of this, VTEX almost always evaluates jobseekers on SQL query questions during interviews for Data Science, Analytics, and & Data Engineering jobs.

Thus, to help you prep, here’s 11 VTEX SQL interview questions – can you answer each one?

11 VTEX SQL Interview Questions

SQL Question 1: Identify Power Users Based on Purchase History

VTEX uses a customer database that tracks purchases made by each customer. As a data analyst, your task is to identify Power Users. A power user, for our case, is defined as a user who makes at least five purchases every month over the past six months. In this problem, you need to write a SQL query that will show the user_id, total number of purchases, and the monthly average for the past six months.

First let's give the structure and example data of table:

Example Input:
1231100101/02/2022 00:00:0020150
1232100202/08/2022 00:00:0020425
1233100103/05/2022 00:00:0020535
1234100304/20/2022 00:00:0020215
1235100205/14/2022 00:00:0020180
1236100106/18/2022 00:00:0020445
1237100207/01/2022 00:00:0020560
1238100105/18/2022 00:00:0020270
1239100106/05/2022 00:00:0020150
1240100107/25/2022 00:00:0020535

We would then want an output that details the power users, the total number of purchases they've made in the last six months, and their average monthly purchases:

Example Output:


The above SQL query first takes the table and groups the number of purchases by and month to create the column. It restricts the timeframe to the past six months. Then we select from this subquery only those users who made at least five purchases in any given month, and generate the total and average number of purchases for each of these power users.

To practice another SQL customer analytics question where you can code right in the browser and have your SQL solution instantly executed, try this Walmart Labs SQL Interview Question: Walmart Labs SQL Interview Question

SQL Question 2: Second Highest Salary

Assume there was a table of VTEX employee salary data. Write a SQL query to find the 2nd highest salary at the company.

VTEX Example Input:


Example Output:


Code your solution to this interview question interactively on DataLemur:

2nd Highest Salary SQL Interview Question


You can find a step-by-step solution here: 2nd Highest Salary.

SQL Question 3: What is a database index, and what are the different types of indexes?

An index in a database is a data structure that helps to quickly find and access specific records in a table.

For example, if you had a database of VTEX customers, you could create a primary index on the column.

Having a primary index on the column can speed up performance in several ways. For example, if you want to retrieve a specific customer record based on their , the database can use the primary index to quickly locate and retrieve the desired record. The primary index acts like a map, allowing the database to quickly find the location of the desired record without having to search through the entire table.

Additionally, a primary index can also be used to enforce the uniqueness of the column, ensuring that no duplicate values are inserted into the table. This can help to prevent errors and maintain the integrity of the data in the table.

VTEX SQL Interview Questions

SQL Question 4: Calculate Monthly Average Star Ratings For Each Product

VTEX is an ecommerce platform and managing product reviews is an important aspect of its functionality. As a part of analysis, we want to calculate the monthly average star ratings for each product.

You have been given a dataset of product reviews which has been recorded as follows:

Example Input:
617112306/08/2022 00:00:00500014
780226506/10/2022 00:00:00698524
529336206/18/2022 00:00:00500013
635219207/26/2022 00:00:00698523
451798107/05/2022 00:00:00698522

Each row contains information such as the review id, the user id, the date the review was submitted, the product id, and the stars given to the product.

Write a SQL query to get the average number of stars for each product for each month in YYYY-MM format.

Example Output:


This query extracts the YYYY-MM part of the submitted date for each review, groups the data by month and product id, and then calculates the average star rating for each group. The part is to round the average to 1 decimal place. The resulting rows are ordered by month and product id.

For more window function practice, try this Uber SQL problem on DataLemur's interactive SQL code editor:

Uber Data Science SQL Interview Question

SQL Question 5: Why would it make sense to denormalize a database?

Database denormalization is when you add redundancy to a database, and break typical normalization rules (specified by 1st, 2nd, 3rd normal forms). There's a few reasons to denormalize a database:

  • Improved performance: Denormalization often reduces the the number of costly join operations that are needed to retrieve data. This is helpful when the database is being used for OLAP (Online Analytical Processing) use cases, as joins can be expensive and slow.

  • Simplification: Denormalization can also be used to simplify the design of a database by reducing the number of tables and relationships that need to be managed. This can make it easier to understand and maintain the database.

  • Ease of use: Denormalization can also make it easier for users to work with a database by providing them with a more intuitive and straightforward data model.

While denormalization can be a useful tool for improving performance and scalability, it's important to keep in mind that it can make update and delete operations more complex. This is because denormalization can create data duplicates, which can make it harder to maintain data integrity. So, to avoid any headaches, it's a good idea to start with a well-normalized database design and then consider denormalization only if it's absolutely necessary for your specific performance and scalability needs. In other words, denormalization can be a bit of a wild card, so it's best to handle it with care!

SQL Question 6: Analyzing Sales Performance

Assume that you are a Data Analyst at VTEX, a company specializing in cloud commerce platform. They have a SQL database containing information on all sales transactions, products, and customers. The database has three main tables:

  1. table that records all customer details.
  2. table that contains details of all products sold.
  3. table that logs all sales transactions.

The company wants to analyze its sales performance and needs to know what was the total revenue obtained per product category in the last month. Your task is to design a SQL query that will generate this information.

Example Input:
Example Input:
Example Input:


This query joins the table with the table on , ensuring we get data for all sales transactions along with the corresponding product information. The condition filters out only those transactions that occurred in the last month. The clause groups the result by product category. The in the statement calculates the total revenue for each group.

SQL Question 7: Why is database normalization a good idea?

Normalization can reduce redundancy and improve performance and flexibility in a database.

By dividing larger tables into smaller, more specific ones linked by foreign keys, it is often possible to improve query speed. Note: it is not always the case that query speed will be improved due to costly nature of joins. Still, we think normalization is a good idea because it can also increase flexibility by making it easier to alter individual tables without affecting others, which can be useful for adapting VTEX's database to ever-changing business needs.

SQL Question 8: Calculating Click-Through-Rate for VTEX products

As a data analyst for VTEX, you've been tasked to examine and report the click-through rates (CTR) for different products from the product view page to the cart page.

The click-through rate is defined as the number of users who add a product to the cart divided by the number of users who viewed the product, expressed as a percentage.

You are provided with two tables - 'views' and 'cart_adds'.

The 'views' table has columns , , , and .

'cart_adds' table has columns , , , and .

Calculate the CTR for each product.

Example Input:
123620106/01/2022 00:00:00501
174852206/10/2022 00:00:00698
223467306/15/2022 00:00:00501
315221307/20/2022 00:00:00698
411798107/25/2022 00:00:00698
Example Input:
131520106/02/2022 00:00:00501
289521307/21/2022 00:00:00698
174052206/12/2022 00:00:00698


This query uses the operation to combine the 'views' and 'cart_adds' tables based on two criteria: matching and . This ensures that the calculation only considers a 'click-through' if the same user viewed and added the same product to the cart.

The function is used to calculate the unique users who viewed and added a product (since one user might view or add a product multiple times). Dividing the number of distinct adds by views and multiplying by 100 gives the CTR in percentage.

The output will provide a list of product ids and their corresponding CTRs.

To practice a related SQL problem on DataLemur's free online SQL code editor, attempt this SQL interview question asked by Facebook: Meta SQL interview question

SQL Question 9: Calculating the Highest Grossing Product Category

VTEX is a company focused on eCommerce platform servicing. Suppose you work at VTEX and you are asked to provide a report about the highest grossing category of products for the last quarter. Your task as a Data Analyst is to write an SQL query to identify the product category that brought in the highest revenue. The sales table stores the transaction information with each product sold, its selling price and the category it belongs to.

Example Input:


This query groups the sales by product categories and calculates the total revenue for each category. It filters the sales for the date range of the last quarter (April, May, June). The result is ordered in descending order of revenue to get the highest grossing category at the top. The LIMIT 1 at the end limits the output to the top grossing category only.

SQL Question 10: In the context of databases, what does atomicity, consistency, isolation, and durability mean?

To ensure the reliability and integrity of data, a database management system (DBMS) strives to maintain the ACID properties: Atomicity, Consistency, Isolation, and Durability. To illustrate these concepts, consider the following examples of how ACID properties apply to banking transactions:

  1. Atomicity: A transaction is either completed in full or not at all. For example, if a customer is transferring money between accounts, the transaction should either transfer the entire amount or none at all.
  2. Consistency: A transaction is only allowed to complete if it follows all rules and constraints within the database. For example, if a customer is withdrawing money from an account, the transaction should only be allowed to proceed if there are sufficient funds available. Otherwise, the transaction is rejected.
  3. Isolation: Concurrent transactions are kept separate from each other, so that the changes made by one transaction cannot be seen by another transaction until the first one is complete. This helps prevent conflicts, such as two customers attempting to withdraw money from the same account at the same time.
  4. Durability: Once a transaction has been committed and completed, the changes made by the transaction are permanently stored in the database and will not be lost even if the database or system crashes. For example, if a customer makes a deposit, the transaction should be durable so that the deposit is not lost in the event of a system failure.

SQL Question 11: Find Customers With Specific Email Domain

In VTEX, our customer records often contain the customer's email address. To reduce complexity, let's only filter based on the email domain (the part after '@'). For example, a common task might be to find all customers who have Gmail accounts.

For this interview question, write a SQL query that extracts all customers from the table whose email address ends with '@gmail.com'.

Example Input:
241John Doejohndoe@gmail.com
978Jane Smithjanesmith@yahoo.com
399Bob Johnsonbob.johnson@gmail.com
652Alice Davisalice.davis@outlook.com
915Charlie Browncharliebrown@gmail.com
Example Output:
241John Doejohndoe@gmail.com
399Bob Johnsonbob.johnson@gmail.com
915Charlie Browncharliebrown@gmail.com


In this PostgreSQL query, we have used the keyword to filter out the customer records where the email address ends with '@gmail.com'. The percent symbol '%' is used as a wildcard in SQL that matches any sequence of characters. So '%@gmail.com' matches any string that ends with '@gmail.com'. The result of the query is a list of customers who have Gmail accounts as per their records in the table.

VTEX SQL Interview Tips

The best way to prepare for a VTEX SQL interview is to practice, practice, practice. Besides solving the above VTEX SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Netflix, Google, and Amazon. DataLemur SQL and Data Science Interview Questions

Each DataLemur SQL question has multiple hints, step-by-step solutions and best of all, there's an online SQL coding environment so you can instantly run your query and have it graded.

To prep for the VTEX SQL interview it is also a great idea to practice SQL questions from other tech companies like:

But if your SQL skills are weak, forget about going right into solving questions – strengthen your SQL foundations with this SQL tutorial for Data Scientists & Analysts.

SQL interview tutorial

This tutorial covers topics including SUM/AVG window functions and working with string/text data – both of which come up frequently during VTEX SQL assessments.

VTEX Data Science Interview Tips

What Do VTEX Data Science Interviews Cover?

Beyond writing SQL queries, the other topics tested in the VTEX Data Science Interview include:

VTEX Data Scientist

How To Prepare for VTEX Data Science Interviews?

I'm a bit biased, but I think the best way to prep for VTEX Data Science interviews is to read the book Ace the Data Science Interview.

The book has 201 data interview questions taken from FAANG & startups. It also has a crash course on SQL, Product-Sense & ML. And finally it's vouched for by the data community, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.

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