10 Tempur Sealy SQL Interview Questions (Updated 2025)

Tempur Sealy employees write SQL queries to analyze sales data by product category, region, and customer segment to predict sales trends and identify opportunities for growth. It is also used to manage and optimize the manufacturing inventory by analyzing customers' purchase behavior data, including repeat business and warranty claims, the reason why Tempur Sealy asks SQL coding questions in interviews for Data Science, Analytics, and & Data Engineering jobs.

Thus, to help you ace the Tempur Sealy SQL interview, here’s 10 Tempur Sealy SQL interview questions in this blog.

10 Tempur Sealy SQL Interview Questions

SQL Question 1: Identify Power Customers for Tempur Sealy

In Tempur Sealy, a company well known for their mattresses and bedding products, power customers are defined as those who have made the highest number of purchases within the last year. As a data analyst, you are required to write a SQL query that lists the top 5 power customers based on the number of purchases.

The database is structured as follows:

customers:

orders:

Your output should list the customer_id, first_name and last_name of the top 5 power customers, as well as the number of orders each customer has placed.

Note: If there are multiple customers with the same number of orders tiebreak by order frequency and then by customer_id in ascending order.

Answer:

SELECT 
  c.customer_id, c.first_name, c.last_name, COUNT(o.order_id) AS num_orders 
FROM 
  customers c 
JOIN
  orders o ON c.customer_id = o.customer_id
WHERE 
  o.order_date >= (CURRENT_DATE - INTERVAL '1 YEAR')
GROUP BY 
  c.customer_id
ORDER BY 
  num_orders DESC, c.customer_id ASC
LIMIT 5;

This query first joins the customers table with the orders table on the customer_id field. It then groups the results by customer, and counts the number of orders each customer has placed within the last year. The results are ordered by number of orders in descending order, and by customer_id in ascending order. Finally, the query returns the top 5 customers with the highest number of orders.

To solve a related customer analytics question on DataLemur's free online SQL code editor, try this recently asked Microsoft SQL interview question:

SQL Question 2: Department vs. Company Salary

Assume you had a table of Tempur Sealy employee salaries, along with which department they belonged to. Write a query to compare the average salary of employees in each department to the company's average salary for March 2024. 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.

Code your solution to this interview question and run your code right in DataLemur's online SQL environment:

The answer is LONG – 30+ lines of SQL. You can find a detailed solution here: Department Salaries.

SQL Question 3: What are the main differences between foreign and primary keys in a database?

To explain the difference between a primary key and foreign key, let's start with an example Tempur Sealy sales database:

tempur_sealy_sales:

In this table, order_id could be a primary key. It is unique for each row in the table and cannot contain null values.

product_id and customer_id could both be foreign keys. They reference the primary keys of other tables, such as a Products table and a Customers table, respectively. This establishes a relationship between the tempur_sealy_sales table and the other tables, such that each row in the sales database corresponds to a specific product and a specific customer.

SQL Question 4: Calculate the Average Monthly Product Rating

Tempur Sealy is a well-known maker of mattresses and related products. They continuously monitor customer reviews and ratings for each product and use this data to improve their offerings. Your task is to write a SQL query that calculates the average rating of each product on a monthly basis.

For simplicity, you can assume that the reviews table has the following schema:

reviews Example Input:

The result should be a table that lists the average rating (stars) for each product (product_id) by month. The output should look like this:

Example Output:

Answer:

Here is one way to write the query using PostgreSQL:

SELECT
  EXTRACT(MONTH FROM submit_date) AS month,
  product_id,
  AVG(stars) AS avg_stars
FROM reviews
GROUP BY month, product_id
ORDER BY month, product_id;

This query uses the EXTRACT function to get the month from the submit_date field. It then groups the records by both month and product, averaging the stars for each group. This result is then ordered by month and product_id to make it easier to interpret.

To solve a similar window function question on DataLemur's free online SQL code editor, solve this Google SQL Interview Question:

SQL Question 5: What's the purpose of the the INTERSECT command?

Similar to the UNION and EXCEPT/MINUS operators, the PostgreSQL INTERSECT operator combines result sets of two or more SELECT statements into a single result set. However, INTERSECT only returns the rows that are in BOTH select statements.

For a concrete example, say you were on the Sales Analytics team at Tempur Sealy, and had data on sales leads exported from both HubSpot and Salesforce CRMs in two different tables. To write a query to analyze leads created after 2023 started, that show up in both CRMs, you would use the INTERSECT command:

SELECT email, job_title, company_id
FROM tempur_sealy_hubspot_leads
WHERE created_at > '2023-01-01'

INTERSECT

SELECT email, job_title, company_id
FROM tempur_sealy_sfdc_leads
WHERE created_at > '2023-01-01';

SQL Question 6: Mattress Sales Analysis

As an analyst at Tempur Sealy, a manufacturing company that develops mattresses, your task is to optimize production planning and marketing efforts. Design a database schema that captures sales data. This should include tables for sales, mattresses, and stores. Use this schema to answer the following questions:

1. Which mattress model is the top selling in terms of units sold and total sales amount?
2. What is the most popular selling store and how many mattresses have they sold?
3. On which day of the week are most mattresses sold?

sales Example Input:

mattresses Example Input:

stores Example Input:

Answer:

The answer to these questions would involve joining tables and aggregating data. Here are the statements for the given questions:

1. Top selling mattress

SELECT m.model_name, SUM(s.units_sold) as total_units, SUM(s.sale_amount) as total_sales
FROM sales s
JOIN mattresses m ON s.mattress_id = m.mattress_id
GROUP BY m.model_name
ORDER BY total_units DESC, total_sales DESC
LIMIT 1;

2. Top selling store

SELECT st.store_name, SUM(s.units_sold) as total_units
FROM sales s
JOIN stores st ON s.store_id = st.store_id
GROUP BY st.store_name
ORDER BY total_units DESC
LIMIT 1;

3. Most popular sale day

SELECT date_part('dow', s.sale_date) as day_of_week, COUNT(*) as total_sales
FROM sales s
GROUP BY day_of_week
ORDER BY total_sales DESC
LIMIT 1;

These queries will answer the questions by aggregating sales data: the sum of units sold and sales amounts, grouped by mattress model name or store name, and then order the results in descending order to identify the top seller. The last query uses the date_part function to extract the day of the week from the date, and then groups data by this to identify the most popular sale day.

SQL Question 7: Could you explain what a self-join is?

A self-join is a JOIN operation in which a single table is joined to itself. To perform a self-join, you must specify the table name twice in the FROM clause, giving each instance a different alias. You can then join the two instances of the table using a JOIN clause, and specify the relationship between the rows in a WHERE clause.

Think of using a self-joins whenever your data analysis involves analyzie pairs of the same things, like comparing the salaries of employees within the same department, or identifying pairs of products that are frequently purchased together (which you can do in this real SQL question from a Walmart interview).

For another self-join example, suppose you were conducting an HR analytics project and needed to examine how frequently employees within the same department at Tempur Sealy interact with one another, you could use a self-join query like the following to retrieve all pairs of Tempur Sealy employees who work in the same department:

SELECT e1.name AS employee1, e2.name AS employee2
FROM tempur_sealy_employees AS e1
JOIN tempur_sealy_employees AS e2 ON e1.department_id = e2.department_id
WHERE e1.id <> e2.id;

This query returns all pairs of Tempur Sealy employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same Tempur Sealy employee being paired with themselves).

SQL Question 8: Filtering Customer Data

As a data analyst at Tempur Sealy, you are required to analyze recent customer transactions. Write a SQL query to filter down a customers database where product_id is 50001 or 69852, the purchase_date is after '06/01/2022' and the purchase_amount is higher than $800.

customers Example Input:

Example Output:

Answer:

SELECT *
FROM customers
WHERE product_id IN (50001, 69852)
AND purchase_date > '06/01/2022' 
AND purchase_amount > 800;

This PostgreSQL query filters down recent customer transactions by product, purchase date, and purchase amount. It uses WHERE to apply the filtering conditions, AND to combine these conditions, and IN to specify multiple possible values for the product_id field.

SQL Question 9: Tempur Sealy Mattress Ratings Average

You are an analyst at Tempur Sealy, a company that deals in mattresses. You have been provided with a table called reviews that contains data on customer reviews for different mattress models. Each row in the table represents one review, and includes the date of the review (submit_date), the unique identifier of the mattress reviewed (product_id), and the rating given by the customer (stars) as an integer between 1 and 5.

Your task is to find the average rating (avg_stars) for each mattress model on a monthly basis.

reviews Example Input:

Example Output:

Answer:

SELECT
    DATE_TRUNC('month', submit_date) AS month,
    product_id,
    AVG(stars) AS avg_stars
FROM
    reviews
GROUP BY
    DATE_TRUNC('month', submit_date),
    product_id;

In this SQL query, we first truncate the submit_date to a monthly basis using the DATE_TRUNC function, which allows us to group by month. We then use the AVG function to find the average stars for each group of reviews, with groups defined by their product_id and month. This gives us the average rating for each product on a monthly basis.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating average ratings or this Wayfair Y-on-Y Growth Rate Question which is similar for using dates in analysis.

SQL Question 10: What do the SQL commands EXCEPT / MINUS do?

The MINUS/EXCEPT operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.

Note that EXCEPT is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't stress about knowing which DBMS supports what exact commands since the interviewers at Tempur Sealy should be lenient!).

Here's a PostgreSQL example of using EXCEPT to find all of Tempur Sealy's Facebook video ads with more than 10k views that aren't also being run on YouTube:

SELECT ad_creative_id
FROM tempur_sealy_facebook_ads
WHERE views > 10000 AND type=video

EXCEPT

SELECT ad_creative_id
FROM tempur_sealy_youtube_ads

If you want to retain duplicates, you can use the EXCEPT ALL operator instead of EXCEPT. The EXCEPT ALL operator will return all rows, including duplicates.

Tempur Sealy SQL Interview Tips

The best way to prepare for a Tempur Sealy SQL interview is to practice, practice, practice. In addition to solving the above Tempur Sealy SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Google, Facebook, Microsoft and Amazon.

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 interactive SQL code editor so you can right in the browser run your SQL query answer and have it checked.

To prep for the Tempur Sealy SQL interview it is also useful to practice SQL problems from other consumer good companies like:

• Leggett & Platt SQL questions
• Church & Dwight SQL questions
• Mattel SQL questions
• Coty SQL questions

But if your SQL coding skills are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this free SQL tutorial.

This tutorial covers things like removing NULLs and creating pairs via SELF-JOINs – both of these show up routinely in Tempur Sealy SQL interviews.

Stay up-to-date on the latest news and developments from Tempur Sealy with their press releases!

Tempur Sealy Data Science Interview Tips

What Do Tempur Sealy Data Science Interviews Cover?

Besides SQL interview questions, the other types of questions to prepare for the Tempur Sealy Data Science Interview are:

• Statistics & Probability Questions
• Coding Questions in Python or R
• Product-Sense and Business Case Questions
• ML Interview Questions
• Resume-Based Behavioral Questions

How To Prepare for Tempur Sealy Data Science Interviews?

I think the optimal way to prepare for Tempur Sealy Data Science interviews is to read the book I wrote: Ace the Data Science Interview.

It covers 201 interview questions sourced from tech companies like Netflix, Google, & Airbnb. 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 got over 1000+ 5-star reviews on Amazon.

While the book is more technical in nature, it's also important to prepare for the Tempur Sealy behavioral interview. Start by reading the company's cultural values.