# 9 Bread Financial SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

At Bread Financial, SQL is used for extracting and analyzing financial data to identify high-risk transactions and predict customer behaviors. It is also used for managing databases to ensure secure storage of sensitive customer information and efficient processing of payment transactions, the reason Bread Financial asks SQL questions during interviews for Data Science, Analytics, and & Data Engineering jobs.

## 9 Bread Financial SQL Interview Questions

### SQL Question 1: Calculate the average loan transaction amount per month for specific users

In Bread Financial, there are several accounts where loan transactions take place regularly. Write a SQL query to analyze the average amount of loan transactions per month for specific users using a dataset with the following fields:

• : The unique identifier of the transaction
• : The unique identifier of the user
• : The date when the transaction occurred
• : The amount of each loan transaction
##### Example Input:
transaction_iduser_idtransaction_dateloan_amount
451712301/15/2022 00:00:0050000
420326501/26/2022 00:00:0020000
348512301/30/2022 00:00:0030000
703936202/18/2022 00:00:0010000
516012302/25/2022 00:00:0060000

We want to analyze this to gain insights into user loan habits for potential special promotions or interventions.

The output should be aggregated monthly, and look like the following:

##### Example Output:
mthuseravg_loan_amount
112340000
126520000
212360000
236210000

This PostgreSQL query uses the function to get the month from the transaction date. Then, it calculates the average loan amount for each user per month with the function. The clause is used to group results by month and user. It further uses the clause to order the results by month and average loan amount in descending order. This enables us to see which users, on average, have the highest loan amounts each month.

Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur

### SQL Question 2: Employees Earning More Than Managers

Given a table of Bread Financial employee salary data, write a SQL query to find all employees who make more than their own boss.

employee_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

#### Example Output:

employee_idemployee_name
3Olivia Smith

This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800. Solve this problem directly within the browser on DataLemur: #### Answer: First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary. If the solution above is tough, you can find a step-by-step solution here: Employees Earning More Than Their Boss. ### SQL Question 3: Could you explain the differences between an inner and full outer join? A full outer join returns all rows from both tables, including any unmatched rows, whereas an inner join only returns rows that match the join condition between the two tables. For a tangible example, suppose you had a table of Bread Financial orders and Bread Financial customers. Here's a SQL inner join using the orders and customers tables: This query will return rows from the orders and customers tables that have matching values. Only rows with matching values will be included in the results. Here is an example of a using the orders and customers tables: This query will return all rows from both the orders and customers tables, including any rows that do not have matching values. Any rows with null values for either table will be included in the results. ### SQL Question 4: Filter Customer Records Bread Financial is interested in knowing the details of its customers who have at least one checking account, no loan account and whose credit card limit is above$5,000. For this purpose, they want to filter the records from the customer database.

Here are the ‘accounts’ and ‘credit_cards’ example database that Bread Financial hold:

##### Example Input:
account_iduser_idaccount_type
10001123checking
10002265savings
10003362checking
10004451loan
10005625checking
##### Example Input:
card_iduser_idcard_typecard_limit
2001123Visa5000
2002265MasterCard8000
2003362Visa4000
2004451MasterCard7000
2005625Visa5500

We need to extract the for those customers who meet the given conditions.

Here is the SQL query that can fulfill this condition in PostgreSQL:

##### Example Output:
loan_statustotal_loan_amount
Approved8500
Rejected14000
Under Review7500

The query for this problem would be,

This query first groups the data in by and then calculates the sum of for each group. This sum is then returned alongside the in the result.

### SQL Question 9: Retrieve Customers with Specific Email Domain

At Bread Financial, the marketing department would like to launch an email campaign specifically targeting customers who use Gmail for personal banking. Your task is to write an SQL query that retrieves all records of customers where the email field ends with "@gmail.com".

##### Example Input:
customer_idfirst_namelast_nameemailaccount_type
129JohnDoejohn.doe@gmail.comPersonal
201SallySmithsally.smith@yahoo.comPersonal
602RebeccaMillsrebecca.mills@gmail.comPersonal

This SQL query uses the keyword to filter down the table by the column. The in the clause is a wildcard character that matches any sequence of characters. So will match any string that ends with "@gmail.com". This will return all customer records where the email ends with "@gmail.com".

### How To Prepare for the Bread Financial SQL Interview

The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. Besides solving the above Bread Financial SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.

Each interview question has hints to guide you, step-by-step solutions and most importantly, there is an online SQL coding environment so you can easily right in the browser your query and have it executed.

To prep for the Bread Financial SQL interview it is also wise to solve SQL questions from other financial services companies like:

Explore the latest happenings at Bread Financial and see how they're making waves in the financial industry!

But if your SQL coding skills are weak, don't worry about going right into solving questions – improve your SQL foundations with this free SQL tutorial.

This tutorial covers SQL topics like CTE vs. Subquery and filtering strings based on patterns – both of these pop up often during Bread Financial SQL assessments.

### Bread Financial Data Science Interview Tips

#### What Do Bread Financial Data Science Interviews Cover?

Besides SQL interview questions, the other question categories tested in the Bread Financial Data Science Interview are:

#### How To Prepare for Bread Financial Data Science Interviews?

To prepare for the Bread Financial Data Science interview have a strong understanding of the company's values and mission – this will be key to acing the behavioral interview. For the technical Data Science interviews, get ready by reading Ace the Data Science Interview. The book's got: