11 Bumble SQL Interview Questions (Updated 2024)

Updated on

March 3, 2024

At Bumble, SQL is typically used for analyzing user behavior patterns for better app functionality, and managing large datasets for targeted, gender-focused marketing strategies. That's why Bumble almost always asks SQL questions in interviews for Data Analyst, Data Science, and BI jobs.

To help you study for the Bumble SQL interview, here’s 11 Bumble SQL interview questions – how many can you solve?

11 Bumble SQL Interview Questions

SQL Question 1: Analyzing Bumble's Power Users

For a dating application like Bumble, a power user might be defined as someone who is very actively using the app. This can mean they are swiping a lot, having many matches, and engaging in conversations frequently. Let's define a Bumble power user as someone who has more than 50 swipes, more than 10 matches, and over 10 conversations in a week.

Given two tables, and , write a SQL query to find all power users for the week of '2022-06-01' to '2022-06-07'.

Example Input:
Example Input:


This query first joins with on the , and then filters the results where activity and match dates fall within the specific week. It then finally filters out users who meet the criteria of a power user, with over 50 swipes, more than 10 matches and more than 10 conversations. The result will be a list of that are the "Power Users".

To practice a related customer analytics question on DataLemur's free interactive SQL code editor, try this recently asked Microsoft SQL interview question: Microsoft SQL Interview Question: Teams Super User

SQL Question 2: User Swipe Analysis

Bumble wants to understand the swipe behavior of its users. You're provided with a dataset that represents swipe actions of various users throughout the day. The dataset contains the following information: user id, time of swipe, and the action(like, pass).

Using SQL, find the average number of swipe actions per hour for each user within a specified time frame. Write a SQL query to address this requirement. Note that, given the dynamic nature of user interactions on the application, some users may not have any swipes within the specified time frame.

Example Input:
10011232022-07-01 14:15:00Like
10021232022-07-01 14:30:00Pass
10032652022-07-01 23:45:00Like
10043622022-07-02 16:00:00Pass
10051232022-07-02 14:15:00Like


This query creates custom time frames within the specified period, counts the number of swipes per user per hour within the time frames, then calculates the average swipes per user per hour. Those users who don't have any swipes within a specific time frame will have their swipe action count as 0 for that hour.

To practice another window function question on DataLemur's free interactive coding environment, try this Google SQL Interview Question: Google SQL Interview Question

SQL Question 3: In the context of a database transaction, what does ACID mean?

A DBMS (database management system), in order to ensure transactions are relaible and don't ruin the integrity of the data, tries to mantain the following ACID properties: Atomicity, Consistency, Isolation, and Durability.

To make this concept more concrete, here is what each of the ACID properties would mean in the context of banking transactions:

  • Atomicity: a transaction is either completed fully, or not complete at all. For example, if a customer is transferring money from one account to another, the transaction should either transfer the full amount or none at all.
  • Consistency: a transaction will only be completed if it follows all database constraints and checks. For example, if a customer is withdrawing money from an account, the transaction should only be completed if the account has sufficient funds available, otherwise the transaction is rejected
  • Isolation: ensures that concurrent transactions are isolated from each other, so that the changes made by one transaction cannot be seen by another transaction. This isolation prevents race conditions, like two customers trying to withdraw money from the same account at the same time.
  • Durability: ensures that once a transaction has been committed and completed, the changes are permanent. A reset / shutdown of the database shouldn't erase someone's savings accounts!

Bumble SQL Interview Questions

SQL Question 4: Analyzing Bumble Date Interactions

Provided the business problem facing Bumble is to analyze and understand the impact of a user activity on match effectiveness. Let's consider two data tables: Users and Matches.

The Users table records the user's information such as ID, gender, premium_status (Premium or Non-Premium). The Matches table records details of every match made on the app, the initiator user, the pair user, the match date, and if a conversation was initiated.

Example Input:
Example Input:

Calculate the conversation initiation rate for Premium and Non-Premium users on Bumble app for the month of July 2022.

Example Output:



In the query above, we join the Users and Matches tables using the user_id. Then we filter the data for the month of July 2022. The COUNT() function is used with a CASE statement to calculate the total number of matches where a conversation was initiated. This count is then divided by the total number of matches to calculate the conversation initiation rate. Finally, we group the result by month and premium status.

SQL Question 5: What's the difference between a one-to-one and one-to-many relationship?

In database schema design, a one-to-one relationship is when each entity is associated with only one instance of the other. For instance, a US citizen's relationship with their social-security number (SSN) is one-to-one because each citizen can only have one SSN, and each SSN belongs to one person.

A one-to-many relationship, on the other hand, is when one entity can be associated with multiple instances of the other entity. An example of this is the relationship between a person and their email addresses - one person can have multiple email addresses, but each email address only belongs to one person.

SQL Question 6: Filter Bumble Users Based on Age, Gender and Last Active

As a Data Analyst at Bumble, you are tasked to filter out active male users who are above 30 years old from the users table. Active users are defined as those who have last logged in within the past month.

The 'users' table contains the following sample data:

Example Input:


This query will return all records from the 'users' table where the user's age is greater than 30, the gender is male, and the last login is within the past month. The current_date function returns the current date, and the 'interval' keyword is used to specify a period of time. In this case, the interval specifies the past month.

SQL Question 7: Can you explain what / SQL commands do?

For a tangible example of in PostgreSQL, suppose you were doing an HR Analytics project for Bumble, and had access to Bumble's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables.

You could use operator to find all contractors who never were a employee using this query:

Note that is available in PostgreSQL and SQL Server, while is the equivalent operator which is available in MySQL and Oracle (but don't worry about knowing which RDBMS supports which exact commands since Bumble interviewers aren't trying to trip you up on memorizing SQL syntax).

SQL Question 8: Average Messaging Activity on Bumble

As an analyst for Bumble, you've been asked to monitor the use of the platform by calculating the average number of messages sent per user each month. This can give insights on user engagement and help shape policies to drive up user interaction.

Example Input:
984214523806/01/2022 14:00:00Hello there!
841710236506/03/2022 16:30:00How's your day?
672914523806/05/2022 10:11:00Let's meet up.
729023814506/06/2022 18:22:00Sure, let's do it.
998310236507/02/2022 20:45:00Sorry, got busy.
Example Output:


Here's the SQL query to find the average messaging activity per month.

The subquery counts the number of messages sent by each user per month using window function. The main query then finds the average count of messages sent across all users for each month. It's important to note here that a month in which no messages were sent won't appear in our final output. We might need to join this result with a calendar table to get a full monthly trend.

To practice a very similar question try this interactive Snapchat Sending vs. Opening Snaps Question which is similar for user engagement metrics or this Twitter Histogram of Tweets Question which is similar for user usage analysis.

SQL Question 9: Click-through-rate (CTR) Calculation for Bumble

Bumble is a dating app where users 'swipe right' or 'swipe left' on other user profiles. If they like someone, they swipe right, showing interest. However, having a match (when two users like each other) is not the end, it's vital to move a conversation beyond just matching. Assume Bumble wants to analyze click-through-rate from viewing to initiating a conversation.

Consider the following tables:

  • : This table records each swipe done by a user. The column will have values "right" for like and "left" for dislike.
  • : This table holds the records of users who initiated a conversation after a match.
Example Input:
110106/01/2022 08:15:002301"right"
232406/01/2022 08:16:002376"left"
343406/01/2022 08:18:002391"right"
421906/01/2022 08:21:002450"right"
510106/01/2022 08:25:002386"left"
Example Input:
1101230106/01/2022 10:12:00
2324237606/01/2022 11:16:00
3219245006/02/2022 08:18:00

Please calculate the click-through-rate as the number of conversations begun after a mutual match (a pair exists in both and tables) over the total swipes made.


Assuming the tables and are located in the schema, the following SQL query can be used:

With this query, we first count the total number of right swipes which indicates likes. Then we join these swipes with the conversations table to count the conversations started after a mutual match. Lastly, we divide the total number of conversations started by the total swipes to get the click-through rate. Please note that data types are adjusted to decimal for more accurate division result.

To practice another question about calculating rates, try this TikTok SQL question within DataLemur's online SQL coding environment: TikTok SQL question

SQL Question 10: What is normalization?

Normalizing a database involves dividing a large table into smaller and more specialized ones, and establishing relationships between them using foreign keys. This reduces repetition, resulting in a database that is more adaptable, scalable, and easy to maintain. Additionally, it helps to preserve the accuracy of the data by reducing the likelihood of inconsistencies and problems.

SQL Question 11: Find the average number of matches per user per month

Bumble is a dating app where users can like and match with each other. The goal of this question is to find the average number of matches each user made per month over the entire lifetime of their account.

Consider the and tables below:

Example Input:
Example Input:


This SQL query joins the and tables on the field, then aggregates data using the clause to calculate the average number of matches per user for every month. The function is used to break down the dates into year and month components for grouping and sorting purposes. is used to calculate the total number of users per month before calculating the average. The result is sorted by year, month, and the average number of matches in descending order.

How To Prepare for the Bumble SQL Interview

The key to acing a Bumble SQL interview is to practice, practice, and then practice some more! In addition to solving the earlier Bumble SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies. DataLemur SQL and Data Science Interview Questions

Each problem on DataLemur has hints to guide you, step-by-step solutions and best of all, there is an interactive coding environment so you can instantly run your SQL query and have it executed.

To prep for the Bumble SQL interview you can also be useful to practice SQL problems from other tech companies like:

In case your SQL query skills are weak, forget about going right into solving questions – go learn SQL with this interactive SQL tutorial.

Interactive SQL tutorial

This tutorial covers SQL concepts such as handling timestamps and GROUP BY – both of these show up often during Bumble SQL interviews.

Bumble Data Science Interview Tips

What Do Bumble Data Science Interviews Cover?

In addition to SQL interview questions, the other question categories to prepare for the Bumble Data Science Interview are:

Bumble Data Scientist

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