9 Lemonade SQL Interview Questions (Updated 2024)

Updated on

June 23, 2024

Data Scientists, Analysts, and Data Engineers at Lemonade write ad-hoc SQL queries as a core part of their job. They use SQL for extracting and analyzing data for automated claims processing, and enhancing customer experience by optimizing insurance underwriting processes. Because of this, Lemonade typically asks folks interviewing for data jobs SQL interview problems.

To help you ace the Lemonade SQL interview, we've collected 9 Lemonade SQL interview questions in this blog.

9 Lemonade SQL Interview Questions

SQL Question 1: Identify Power Users Based on Total Purchase Amount

Lemonade is an e-commerce company that sells a variety of products to customers. They consider a user as a 'Power User' if their total purchase amount exceeds $5000 within the last 3 months.

Given the table below, write a SQL query to generate a list of 'Power Users', their total purchase amount within the last 3 months and their corresponding email.

The table is structured as follows:

Sample Input:

The table is structured as follows:

Sample Input:


This query first creates a subquery () to summarize the total purchase amounts within the last 3 months for each user.

Then it joins the table and the subquery on to get the corresponding email addresses of the users.

Finally, it filters out the users whose total purchase amount exceeds $5000, which qualifies them as 'Power Users', and orders the resulting data in descending order of the total purchase amount.

To solve a related super-user data analysis question on DataLemur's free interactive coding environment, try this Microsoft Teams Power User SQL Interview Question: Microsoft SQL Interview Question: Teams Super User

SQL Question 2: Department vs. Company Salary

Assume there was a table of Lemonade employee salaries, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.

Try this question interactively on DataLemur:

Department vs. Company Salary

The solution is LONG – 30+ lines of SQL. You can find a detailed solution with hints here: Department vs. Company Salary.

SQL Question 3: Could you describe the function of UNION in SQL?


The operator merges the output of two or more statements into a single result set. The two SELECT statements within the UNION must have the same number of columns and the data types of the columns are all compatible.

For example, if you were a Data Analyst on the marketing analytics team at Lemonade, this statement would return a combined result set of both Lemonade's Google and Facebook ads that have more than 300 impressions:

Lemonade SQL Interview Questions

SQL Question 4: Average Stars Per Product Per Month

Lemonade, a company primarily engaging in insurance services, recently diversified its product offerings. This led to an increase in customer reviews for their various products.

Your task is to write a SQL query to calculate the average star rating for each product on a monthly basis for 2022.

Assume a dataset named with the following structure:

Example Input:

The query should yield the following output table:

Example Output:


This PostgreSQL query extracts the month from the . It averages the for each by month using a GROUP BY clause. The WHERE clause is used to filter reviews only for the year 2022. The GROUP BY clause ensures that the average is calculated separately for each month and product.

To practice a similar window function interview problem which uses RANK() on DataLemur's free online SQL coding environment, solve this Amazon SQL Interview Question: Amazon Business Intelligence SQL Question

SQL Question 5: What is the process for finding records in one table that do not exist in another?

To identify records in one table that do not appear in another, you can use a LEFT JOIN and examine NULL values in the right-side table.

Say for example you had exported Lemonade's CRM (Customer Relationship Management) database into PostgreSQL, and had a table of sales leads, and a second table of companies.

Here's an example of how a query could find all sales leads that are not associated with a company:

This query brings back all rows from the sales leads table, along with any matching rows from the companies table. If there is no matching row in the companies table, NULL values will be returned for all of the right table's columns.

We then filter out out any rows where the column is , leaving only the sales leads that are NOT associated with a company.

SQL Question 6: Calculate the total revenue from each flavor of lemonade

Given a table named that tracks the transactions for a company named Lemonade, write a query that returns the total revenue generated from each flavor of lemonade.

Each row in the table represents a unique sale and contains the following columns:

  • (integer): A unique identifier for each transaction.
  • (integer): The id for each customer.
  • (date): The date of the transaction.
  • (string): The flavor of lemonade sold (e.g., "Original", "Strawberry", "Mango").
  • (float): The price of each lemonade sold.
Example Input:


This query sums all prices for each distinct flavor in the table. It then returns a result with each flavor and its corresponding total revenue. This provides insight into the revenue performance of each flavor of lemonade.

Example Output:

SQL Question 7: Can you describe the meaning of a constraint in SQL in layman's terms?

Constraints are used to specify the rules concerning data in the table. It can be applied for single or multiple fields in an SQL table during the creation of the table or after creating using the ALTER TABLE command. The constraints are:

Say you were storing sales analytyics data from Lemonade's CRM inside a database. Here's some example constraints you could use:

  • PRIMARY KEY constraint: You might use a PRIMARY KEY constraint to ensure that each record in the database has a unique identifier. For example, you could use the "opportunity_id" field as the primary key in the "opportunities" table.

  • FOREIGN KEY constraint: You might use a FOREIGN KEY constraint to link the data in one table to the data in another table. For example, you could use a foreign key field in the "opportunities" table to reference the "account_id" field in the "accounts" table.

  • NOT NULL constraint: You might use a NOT NULL constraint to ensure that a field cannot contain a NULL value. For example, you could use a NOT NULL constraint on the "opportunity_name" field in the "opportunities" table to ensure that each opportunity has a name.

  • UNIQUE constraint: You might use a UNIQUE constraint to ensure that the data in a field is unique across the entire table. For example, you could use a UNIQUE constraint on the "email" field in the "contacts" table to ensure that each contact has a unique email address.

  • CHECK constraint: You might use a CHECK constraint to ensure that the data in a field meets certain conditions. For example, you could use a CHECK constraint to ensure that the "deal_probability" field in the "opportunities" table is a value between 0 and 100.

  • DEFAULT constraint: You might use a DEFAULT constraint to specify a default value for a field. For example, you could use a DEFAULT constraint on the "stage" field in the "opportunities" table to set the default value to "prospecting"

SQL Question 8: Filter Customer Data from Lemonade Company

The Lemonade company is looking to send out targeted email offers to its customers and need help filtering the data. They specifically want to find all customers from the table who live in the cities or regions that start with 'San'.

Table (Example Input):
1001John Doejohndoe@gmail.com123 StreetSan Francisco
1002Jane Smithjanesmith@gmail.com456 AvenueSan Diego
1003David Johnsondavidjohnson@hotmail.com789 LaneLos Angeles
1004Sarah Brownsarahbrown@yahoo.com321 BoulevardSanta Clara
1005James Whitejameswhite@gmail.com654 DriveSacramento
Example Output (Expected Result):
1001John Doejohndoe@gmail.com123 StreetSan Francisco
1002Jane Smithjanesmith@gmail.com456 AvenueSan Diego
1004Sarah Brownsarahbrown@yahoo.com321 BoulevardSanta Clara


This SQL query uses the keyword with the wildcard character () to filter out all records in the table where the starts with 'San'. Records where the starts with any other string will not match this condition and will not be returned in the result. Note that the symbol is used to represent zero, one or multiple characters.

SQL Question 9: Calculation of Revenue and Profit Margin

Lemonade Inc, an insurance company, needs to calculate the total revenue and profit margin from each insurance policy it sold last quarter. The revenue is calculated by taking the premiums paid by the customers. The profit margin is calculated as (revenue - claim amount) / revenue.

You have two tables - Policies and Claims. The 'Policies' table has the following fields: policy_id (integer), customer_id (integer), premium (double), type (text). Premium is the amount the customer pays for their policy.

The 'Claims' table has the following fields: claim_id (integer), policy_id (integer), amount (double). Amount is the total claim amount.

Write a PostgreSQL query to calculate the total revenue, total claims, and profit margin for each type of insurance policy sold by Lemonade.

Example Input:
501123200.50Car Inc.
502124300.00Home Inc.
503125400.00Car Inc.
504126200.00Pet Inc.
Example Input:
Example Output:
Car Inc.600.50250.0058.37%
Home Inc.300.00150.0050.00%
Pet Inc.200.0050.0075.00%


In this query, we are joining the 'Policies' and 'Claims' tables using the policy_id. Then, we are grouping the data by the policy type to calculate the total revenue, total claims, and profit margin for each type of policy. The ROUND function is used to limit the decimal places of the profit margin to two, and we've then concatenated '%' to present the profit margin as a percentage.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating highest value items or this CVS Health Pharmacy Analytics (Part 1) Question which is similar for analyzing profit margins.

Preparing For The Lemonade SQL Interview

The key to acing a Lemonade SQL interview is to practice, practice, and then practice some more! Beyond just solving the earlier Lemonade SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like FAANG tech companies and tech startups. DataLemur Questions

Each DataLemur SQL question has multiple hints, detailed solutions and most importantly, there's an online SQL code editor so you can instantly run your SQL query answer and have it graded.

To prep for the Lemonade SQL interview you can also be a great idea to solve interview questions from other tech companies like:

However, if your SQL coding skills are weak, forget about diving straight into solving questions – improve your SQL foundations with this DataLemur SQL Tutorial.

SQL tutorial for Data Analytics

This tutorial covers SQL topics like aggreage functions like MIN()/MAX() and WHERE with AND/OR/NOT – both of these pop up often in SQL job interviews at Lemonade.

Lemonade Data Science Interview Tips

What Do Lemonade Data Science Interviews Cover?

Beyond writing SQL queries, the other topics to prepare for the Lemonade Data Science Interview are:

  • Probability & Stats Questions
  • Python Pandas or R Coding Questions
  • Data Case Study Questions
  • Machine Learning and Predictive Modeling Questions
  • Behavioral Interview Questions

Lemonade Data Scientist

How To Prepare for Lemonade Data Science Interviews?

I'm a bit biased, but I think the best way to study for Lemonade Data Science interviews is to read the book I wrote: Ace the Data Science Interview.

The book has 201 data interview questions taken from FAANG, tech startups, and Wall Street. It also has a crash course on SQL, Product-Sense & ML. And finally it's helped thousands of people land their dream job in data, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.

Ace the DS Interview