9 Estée Lauder SQL Interview Questions (Updated 2025)
At Estée Lauder, SQL is crucial for analyze customer behavior data by segmenting demographics, tracking purchase history, and identifying loyalty patterns to personalize marketing strategies. It is also used for managing large datasets related to product performance by monitoring sales metrics, customer feedback, and product lifecycle analysis for continuous business improvement, resulting Estée Lauder to ask SQL questions during interviews for Data Analyst, Data Science, and BI jobs.
To help you ace the Estée Lauder SQL interview, we've curated 9 Estée Lauder SQL interview questions – scroll down to start solving them!
9 Estée Lauder SQL Interview Questions
SQL Question 1: Find the Top Purchasing Customers at Estée Lauder
Estée Lauder is a company that specializes in prestige skincare, makeup, fragrance and hair care products. The sales team is interested in identifying their top customers. They define top customers as those who purchased the most products in terms of quantity. Specifically, they want a list of the top 5 customers who purchased the most within the last 6 months. The list should display the user id, total quantity, and total amount spent by the user.
The sales data is stored in a 'purchases' table with the following structure:
Example:
| purchase_id | user_id | purchase_date | product_id | quantity | amount |
|---|---|---|---|---|---|
| 101 | 303 | 06/08/2022 00:00:00 | 6001 | 8 | 200 |
| 102 | 305 | 06/10/2022 00:00:00 | 7001 | 6 | 250 |
| 103 | 303 | 06/18/2022 00:00:00 | 6001 | 10 | 250 |
| 104 | 306 | 07/26/2022 00:00:00 | 8001 | 5 | 150 |
| 105 | 303 | 07/05/2022 00:00:00 | 7001 | 7 | 200 |
Answer:
We can use a subquery to filter purchases that occurred in the last 6 months, and then group by user id to get the total quantity and amount spent by each user. The result set is then ordered by total quantity in descending order and limited to top 5 users.
The above query first filters out purchases that are older than 6 months. It then groups the remaining purchases by user id and calculates the total quantity and price for each user. The result set is ordered by total quantity in descending order, and only the top 5 users are selected. In case of a tie on total quantity, the query would favor the user who has the higher total amount spent.
To practice a super-customer analysis question on DataLemur's free online SQL coding environment, try this Microsoft SQL Interview problem:
SQL Question 2: Well Paid Employees
Given a table of Estée Lauder employee salaries, write a SQL query to find employees who earn more money than their own manager.
Estée Lauder Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
Check your SQL query for this problem interactively 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 code above is tough, you can find a step-by-step solution with hints here: Employee Salaries Higher Than Their Manager.
SQL Question 3: How does an inner join differ from a full outer join?
An inner join only includes rows from both tables that satisfy the join condition, whereas a full outer join includes all rows from both tables, regardless of whether they match the join condition or not.
To demonstrate each kind, Imagine you were working on a Advertising Analytics project at Estée Lauder and had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.
An retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.
A retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
SQL Question 4: Average Monthly Product Ratings
Estée Lauder is a global leader in prestige beauty. The company wants to understand how customers rate their beauty products on a monthly basis. Using the table containing review_id, user_id, submit_date, product_id, and stars (where stars range from 1 to 5), can you write a query that calculates the average product rating per month for each product?
We can use the PostgreSQL window functions to solve this problem. In SQL, a window function performs a calculation across a set of table rows that are related to the current row.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Example Output:
| mth | product_id | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
Answer:
Here is a PostgreSQL query that calculates the average product rating per month for each product:
This query partitions data by month and product_id using the clause within the window function. Then, it calculates the average using the function, and orders the result by and .
Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur
SQL Question 5: What's a constraint in SQL, and do you have any examples?
In a database, constraints are rules that the DBMS (database management system) follows when performing operations such as inserting, updating, or deleting data.
For example, consider a table of employee records at Estée Lauder. Some constraints that you might want to implement include:
-
NOT NULL: This constraint ensures that certain columns, such as the employee's first and last name, cannot be NULL.
-
UNIQUE: This constraint ensures that each employee has a unique employee ID.
-
PRIMARY KEY: This constraint combines the NOT NULL and UNIQUE constraints to create a primary key for the employee table. The primary key is a column or set of columns that uniquely identifies each row in the table.
-
FOREIGN KEY: This constraint establishes a relationship between the employee table and other tables in the database. For example, you could use a foreign key to link the employee ID to the department ID in a department table to track which department each employee belongs to.
-
DEFAULT: This constraint specifies a default value for a column in case no value is specified when a new row is inserted into the table.
SQL Question 6: Average Sales Per Product Category
Estée Lauder is a notable name in premium skincare, makeup, and fragrance products. As a Data Analyst in the Estée Lauder company, you are tasked to determine the average sales per product category for the last quarter. Determine the product category that has the highest average sales in this period.
Example Input:
| sale_id | product_id | sale_date | units_sold | price_per_unit |
|---|---|---|---|---|
| 8694 | 105 | 06/28/2022 | 20 | 50 |
| 4096 | 210 | 07/15/2022 | 15 | 75 |
| 5721 | 315 | 08/07/2022 | 25 | 60 |
| 1665 | 105 | 09/02/2022 | 30 | 50 |
| 3816 | 315 | 09/23/2022 | 40 | 60 |
Example Input:
| product_id | product_category |
|---|---|
| 105 | Skincare |
| 210 | Makeup |
| 315 | Fragrance |
Example Output:
| Product Category | Average Sales |
|---|---|
| Skincare | 1800 |
| Makeup | 1125 |
| Fragrance | 2250 |
Answer:
This query joins the sales and products tables based on the product_id. It selects only the sales made in the last quarter (3rd quarter). The average sales (product of units sold and price per unit) are computed for each product category. Finally, the results are ordered in descending order of the average sales.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for needing to calculate highest sales categories or this Wayfair Y-on-Y Growth Rate Question which is similar for involving sales data analysis.
SQL Question 7: What do foreign key's do?
A foreign key is a field in a database table that links to the primary key of another table, establishing a connection between the two tables. For example, let's analyze Estée Lauder's Google Ads campaigns data:
:
| ad_id | campaign_id | keyword | click_count |
|---|---|---|---|
| 1 | 201 | Estée Lauder reviews | 120 |
| 2 | 202 | Estée Lauder pricing | 150 |
| 3 | 101 | buy Estée Lauder | 65 |
| 4 | 101 | Estée Lauder alternatives | 135 |
is a foreign key that connects to the of the corresponding Google Ads campaign. This establishes a relationship between the ads and their campaigns, enabling easy querying to find which ads belong to a specific campaign or which campaigns a specific ad belongs to.
The table may also have multiple foreign keys that reference primary keys in other tables. For example, and foreign keys could be used to link each ad to its ad group and the Google Ads account that the campaigns belong to, respectively.
SQL Question 8: Find Customers with a Specific Pattern in their Name
For the company Estée Lauder, we have a database of customers and their purchases. The goal is to retrieve the list of customers whose first name starts with a certain letter or letters. For instance, you are asked to find all customers whose first name starts with 'An'. Then, provide the total number of products they have purchased.
Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 001 | Annie | Johnson | annie.johnson@example.com |
| 002 | Ann | Smith | ann.smith@example.com |
| 003 | John | Doe | john.doe@example.com |
| 004 | Andrew | McDonald | andrew.mcdonald@example.com |
| 005 | James | Williams | james.williams@example.com |
Example Input:
| purchase_id | customer_id | product_id | quantity |
|---|---|---|---|
| 1001 | 001 | 2001 | 3 |
| 1002 | 001 | 2002 | 2 |
| 1003 | 002 | 2001 | 1 |
| 1004 | 002 | 2003 | 1 |
| 1005 | 004 | 2002 | 2 |
| 1006 | 003 | 2003 | 1 |
| 1007 | 005 | 2001 | 2 |
Example Output:
| first_name | total_products_purchased |
|---|---|
| Annie | 5 |
| Ann | 2 |
| Andrew | 2 |
Answer:
The SQL query above first joins the table with the table using the . Then it filters out the customers whose starts with 'An' using the operator. Finally, it groups the results by and calculates the total products each customer has purchased using .
SQL Question 9: Analyzing and Joining Customer and Purchase Data
Estée Lauder has two tables, and . The table has columns , , , , , and . The table has columns , , , , and .
Write a query to find the total purchase amount of each customer along with their full names and email.
Note: Not every customer in the table will necessarily have purchases.
Example Input:
| customer_id | firstname | lastname | city | state | |
|---|---|---|---|---|---|
| 1 | John | Doe | johndoe@example.com | New York | NY |
| 2 | Mary | Johnson | maryj@example.com | Los Angeles | CA |
| 3 | James | Smith | jamessmith@example.com | Chicago | Il |
| 4 | Patricia | Williams | patriciaw@example.com | Houston | TX |
Example Input:
| purchase_id | product_id | customer_id | purchase_date | amount |
|---|---|---|---|---|
| 1 | 1001 | 1 | 2022-01-25 | 200.00 |
| 2 | 1002 | 1 | 2022-02-15 | 350.00 |
| 3 | 1003 | 2 | 2022-03-02 | 150.00 |
| 4 | 1004 | 3 | 2022-02-20 | 175.00 |
| 5 | 1005 | 3 | 2022-03-05 | 225.00 |
| 6 | 1006 | 4 | 2022-02-27 | 300.00 |
Answer:
This query joins the table with the table on the field. A full name is constructed by concatenating and . We use to ensure that if a customer has made no purchases ( is null), the total purchase amount is reported as 0. Finally, the results are ordered by in descending order to find the customers with the highest total purchase amount first.
Because joins come up frequently during SQL interviews, practice an interactive SQL join question from Spotify:
How To Prepare for the Estée Lauder SQL Interview
The best way to prepare for a Estée Lauder SQL interview is to practice, practice, practice. Beyond just solving the above Estée Lauder SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each DataLemur SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there is an online SQL code editor so you can right online code up your SQL query answer and have it graded.
To prep for the Estée Lauder SQL interview you can also be a great idea to practice interview questions from other consumer good companies like:
- Stanley Black & Decker SQL questions
- Colgate-Palmolive SQL questions
- Kimberly-Clark SQL questions
- Procter & Gamble SQL questions
Dive into the world of beauty and innovation with Estee Lauder's newsroom!
However, if your SQL query skills are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers things like handling missing data (NULLs) and inner vs. outer JOIN – both of which show up often during SQL interviews at Estée Lauder.
Estée Lauder Data Science Interview Tips
What Do Estée Lauder Data Science Interviews Cover?
In addition to SQL interview questions, the other types of questions to prepare for the Estée Lauder Data Science Interview include:
- Statistics and AB Testing Questions
- Python or R Programming Questions
- Product Analytics Questions
- Machine Learning Questions
- Behavioral & Resume-Based Questions
How To Prepare for Estée Lauder Data Science Interviews?
I think the optimal way to study for Estée Lauder Data Science interviews is to read the book Ace the Data Science Interview.
It solves 201 data interview questions taken from Microsoft, Amazon & startups. The book's also got a refresher covering 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.
While the book is more technical in nature, it's also important to prepare for the Estée Lauder behavioral interview. Start by reading the company's culture and values.