At Flywire, SQL is typically used for analyzing and reporting on international payment transaction data, and maintaining the customer financial database for optimized payment solutions. Unsurprisingly this is why Flywire asks SQL query questions during interviews for Data Analyst, Data Science, and BI jobs.
So, to help you prepare for the Flywire SQL interview, this blog covers 10 Flywire SQL interview questions – able to answer them all?
Flywire is an international payment solution. One day, the data scientist team wants to know the monthly average transaction amount for each country to identify the trends and patterns. They provide you with the following dataset and ask you to write a SQL query using window functions to calculate the monthly average transaction amount for each country, sorted by country and year-month in ascending order.
transaction_id | client_id | transaction_date | country | transaction_amount |
---|---|---|---|---|
2359 | 343 | 2022-01-15 | USA | 250.50 |
4920 | 157 | 2022-02-06 | CAN | 500.00 |
2134 | 896 | 2022-01-22 | CAN | 233.00 |
6532 | 920 | 2022-02-14 | USA | 460.75 |
9123 | 125 | 2022-02-25 | CAN | 600.00 |
This SQL query first creates a window for each month and country, then calculates the average transaction amount within each window. The result is then grouped by country and year-month. Finally, the result is ordered by country and year-month in ascending order. The function is used to limit the average transaction amount to two decimal places.
To practice a related window function SQL problem on DataLemur's free online SQL code editor, solve this Google SQL Interview Question:
Flywire serves millions of clients facilitating cross-border transactions. You have two tables containing relevant data. One table, 'clients', contains their user_id, client name and country. Another table, 'transactions', includes each transaction's id, the sender's user_id, the receiver's user_id, the transaction's date and transaction's amount.
Design a SQL query that will output the total transactions amount each client has received per month, sorted by the transaction amount in descending order.
user_id | client_name | country |
---|---|---|
1 | John S. | USA |
2 | Maria G. | Spain |
3 | Tom K. | UK |
4 | Sophia L. | Canada |
transaction_id | sender_id | receiver_id | transaction_date | transaction_amount |
---|---|---|---|---|
1 | 1 | 2 | 06/08/2022 | 500 |
2 | 3 | 1 | 06/08/2022 | 1000 |
3 | 1 | 3 | 06/08/2022 | 400 |
4 | 2 | 4 | 06/09/2022 | 600 |
5 | 4 | 1 | 07/10/2022 | 350 |
6 | 3 | 2 | 07/15/2022 | 1200 |
7 | 4 | 3 | 07/20/2022 | 700 |
The following PostgreSQL query can be used to answer this question:
In this query, first a CTE (Common Table Expression) named is created to aggregate the total transaction amount that each user has received per month. Then, this CTE is joined with table on receiver_id to get the client's name. The final list is sorted by the transaction amount in descending order to arrange the clients according to how much they have received.
If you want to return records with no duplicates, you can use the keyword in your statement.
For example, if you had a table of Flywire employees, and wanted to see what are all the unique job titles that currently worked at the company, you could write the following query:
If had the following data:
f_name | job_title |
---|---|
Akash | Data Analyst |
Brittany | Data Scientist |
Carlos | Data Engineer |
Diego | Data Engineer |
Eva | Data Analyst |
Then the output from the query would be:
job_title |
---|
Data Analyst |
Data Scientist |
Data Engineer |
Flywire, a global payment solution company, is interested to understand more about their transactions. Your task is to calculate the average transaction amount for each type of currency over a certain period.
transaction_id | transaction_date | currency | amount |
---|---|---|---|
101 | 01/02/2022 | USD | 250.00 |
305 | 01/07/2022 | EUR | 150.00 |
803 | 02/11/2022 | USD | 500.00 |
204 | 02/21/2022 | EUR | 300.00 |
505 | 02/29/2022 | GBP | 100.00 |
month | currency | avg_transaction |
---|---|---|
1 | USD | 250.00 |
1 | EUR | 150.00 |
2 | USD | 500.00 |
2 | EUR | 300.00 |
2 | GBP | 100.00 |
This PostgreSQL query uses the function to calculate the average transaction amount by currency and month. The function is applied to the column to extract the month of the transactions. The result is grouped by currency and month and ordered by month and currency for easy reading.
To practice a very similar question try this interactive Stripe Repeated Payments Question which is similar for requiring analysis of transaction data or this Uber User's Third Transaction Question which is similar for focusing on individual transaction records.
is used to combine the results of multiple statements into a single result set.
Suppose you were doing an HR Analytics project for Flywire, and needed to analyze both Flywire's contractors and employees. You could use in the following way:
This statement would return a combined result set of Flywire contractors and employees who were hired after the start of the year 2023.
Flywire has been running different marketing campaigns to attract more customers. For each ad displayed to a user, Flywire tracks whether the user clicked on the ad and whether the user subsequently purchased a service after clicking the ad.
Given two tables and , calculate the click-through rate (CTR) and the conversion rate. The click-through rate is defined as the number of clicks divided by the number of impressions, and the conversion rate is defined as the number of purchases divided by the number of clicks.
Assume we track the following information:
table:
table:
ad_id | user_id | timestamp | clicked |
---|---|---|---|
101 | 123 | 06/08/2022 00:00:00 | 1 |
102 | 265 | 06/10/2022 00:00:00 | 0 |
103 | 362 | 06/18/2022 00:00:00 | 1 |
104 | 192 | 07/26/2022 00:00:00 | 0 |
105 | 981 | 07/05/2022 00:00:00 | 1 |
purchase_id | user_id | ad_id | timestamp |
---|---|---|---|
1001 | 123 | 101 | 06/08/2022 01:00:00 |
1002 | 362 | 103 | 06/18/2022 02:00:00 |
1003 | 981 | 105 | 07/05/2022 03:00:00 |
In the SQL query, we first join 'ads' and 'purchases' table on 'ad_id' and 'user_id' to combine the click and purchase information for each user.
Then in the SELECT clause:
To solve a similar problem about calculating rates, solve this TikTok SQL question within DataLemur's online SQL code editor:
{#Question-7}
In SQL, a value is NOT the same as a zero or a blank space. A NULL value represents the absence of a value or a missing value, whereas both zero and blank space are actually values.
To handle nulls, the function is often used to check for a null, and if there is a null, you can assign a default value.
Flywire facilitates international payments. As part of a business review, you need to understand the average transaction value per country over a certain period (e.g., monthly basis). This could help to identify countries with high-value transactions, a potentially interesting piece of information for the business strategy.
transaction_id | user_id | transaction_date | country_id | amount |
---|---|---|---|---|
1 | 345 | 06/10/2022 00:00:00 | 101 | 3000 |
2 | 567 | 06/10/2022 00:00:00 | 101 | 4000 |
3 | 890 | 06/20/2022 00:00:00 | 102 | 5000 |
4 | 567 | 07/10/2022 00:00:00 | 101 | 4000 |
5 | 890 | 07/20/2022 00:00:00 | 102 | 9000 |
mth | country | avg_transaction |
---|---|---|
6 | 101 | 3500 |
6 | 102 | 5000 |
7 | 101 | 4000 |
7 | 102 | 9000 |
This SQL query does the following:
As a data analyst at Flywire, you've been tasked with retrieving customer records from the company database. Specifically, the marketing team is running a promotional event for customers with Gmail addresses. They want a list of all customers whose emails are registered with Gmail. Write a SQL query to filter the customer data and output these details: customer id, customer name, and email id.
customer_id | customer_name | email_id |
---|---|---|
001 | John Doe | john.doe@gmail.com |
002 | Jane Smith | janesmith@yahoo.com |
003 | James Brown | jbrown@hotmail.com |
004 | Jessica Jones | jjones@gmail.com |
005 | Tom Hanks | tom.hanks@yahoo.com |
customer_id | customer_name | email_id |
---|---|---|
001 | John Doe | john.doe@gmail.com |
004 | Jessica Jones | jjones@gmail.com |
This SQL query uses the LIKE operator to filter and return records from the customers table where the 'email_id' ends with '@gmail.com', indicating the customer is using a Gmail account. The percentage sign (%) serves as a wildcard character, which means any characters can precede '@gmail.com'.
"One creative way is to use the window function ROW_NUMBER() and partition by whichver columns you are loooking for duplicates in. If any row has a row_number() more than 1, then it's a duplicate!
You could also use COUNT(DISTINCT col1) vs. COUNT(*) and see if they return different numbers, indicating the prescence of duplicates!
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. Beyond just solving the earlier Flywire SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Microsoft, Google, and Facebook.
Each DataLemur SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive SQL code editor so you can right online code up your query and have it graded.
To prep for the Flywire SQL interview you can also be useful to practice SQL problems from other tech companies like:
In case your SQL foundations are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers SQL concepts such as finding NULLs and window functions like RANK() and ROW_NUMBER() – both of these come up routinely in Flywire interviews.
In addition to SQL interview questions, the other types of problems to practice for the Flywire Data Science Interview are:
The best way to prepare for Flywire Data Science interviews is by reading Ace the Data Science Interview. The book's got: