9 Lithia Motors SQL Interview Questions (Updated 2024)
Data Science, Data Engineering and Data Analytics employees at Lithia Motors use SQL for analyzing sales trends across different dealerships and optimizing inventory management based on customer purchasing behavior. That's why Lithia Motors usually asks SQL interview problems.
So, to help you prepare, we've curated 9 Lithia Motors SQL interview questions – can you answer each one?
9 Lithia Motors SQL Interview Questions
SQL Question 1: Sales Analysis using Window Function
Given a fictional dataset of car sales at Lithia Motors, write a SQL query to retrieve the total sales of each car model per month, and rank them within each month based on the volume of sales. A higher rank means more sales volume. Use a window function for this task.
Please note that the 'sale_date' format is 'YYYY-MM-DD' and the sales are recorded when the sales transaction has been fully completed.
Example Input:
| sale_id | sale_date | car_model | sale_amount |
|---|---|---|---|
| 1 | 2023-01-15 | Ford F150 | 30000 |
| 2 | 2023-01-22 | Toyota Camry | 27000 |
| 3 | 2023-01-30 | Toyota Camry | 27000 |
| 4 | 2023-02-05 | Chevrolet Silverado | 28000 |
| 5 | 2023-02-12 | Ford F150 | 30000 |
| 6 | 2023-02-20 | Chevrolet Silverado | 28000 |
| 7 | 2023-02-28 | Ford F150 | 30000 |
| 8 | 2023-02-28 | Toyota Camry | 27000 |
Expected Output:
| month | car_model | total_sales | monthly_rank |
|---|---|---|---|
| 1 | Toyota Camry | 54000 | 1 |
| 1 | Ford F150 | 30000 | 2 |
| 2 | Ford F150 | 60000 | 1 |
| 2 | Chevrolet Silverado | 56000 | 2 |
| 2 | Toyota Camry | 27000 | 3 |
Answer:
We can use window functions and aggregations like SUM, RANK for solving this question. Below is a PostgreSQL query:
This query will first sum up the sales for each model for every month. It then ranks these summed sales within each month, with higher sales getting a higher rank (1 being highest). The final result is ordered by the month and rank.
To practice another window function question on DataLemur's free interactive coding environment, solve this Amazon SQL question asked in a BI Engineer interview:
SQL Question 2: Department Salaries
You're given a table of Lithia Motors employee and department salaries. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.
Try this problem interactively on DataLemur:
The solution is LONG – 30+ lines of SQL. You can find a step-by-step solution here: Department Salaries.
SQL Question 3: Name the different types of joins in SQL. What does each one do?
Joins in SQL allow you to combine data from different tables based on a shared key or set of keys.
Four JOIN types are available in SQL. For an example of each one, say you had sales data exported from Lithia Motors's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .
- : retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the Sales table and the Customers table would retrieve only the rows where the customer_id in the Sales table matches the customer_id in the table.
- : retrieves all rows from the left table (in this case, the sales table) and any matching rows from the right table (the table). If there is no match in the right table, NULL values will be returned for the right table's columns.
- : retrieves all rows from the right table (in this case, the customers table) and any matching rows from the left table (the sales table). If there is no match in the left table, NULL values will be returned for the left table's columns.
- : retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be returned for the columns of the non-matching table.
Check out the Lithia Motors career page and see where you fit best in the company!
SQL Question 4: Analyzing Car Sales Data
Lithia Motors, one of the largest automotive retailers in the United States, wants to better understand their car sales for strategic decision-making. You as a data analyst are supposed to help in this.
They are interested in knowing which car models are most popular among customers and what the average car sale price is for each car model. They have two main tables:
- – stores information about each car sale
- - stores information about each car model
Example Input:
| sale_id | car_model_id | sale_price | sale_date |
|---|---|---|---|
| 1001 | 12 | $20,000 | 01/01/2022 |
| 1002 | 15 | $30,000 | 01/02/2022 |
| 1003 | 12 | $25,000 | 01/05/2022 |
| 1004 | 20 | $40,000 | 01/10/2022 |
| 1005 | 27 | $35,000 | 01/15/2022 |
Example Input:
| car_model_id | car_model_name |
|---|---|
| 12 | Toyota Camry |
| 15 | Honda Accord |
| 20 | BMW X5 |
| 27 | Audi A4 |
The data needs to answer the following questions:
- Calculate the total number of sales per car model.
- Calculate the average sale price per car model.
Answer:
You can use the SQL JOIN operation to combine rows from these tables. You can then group by car model name to calculate the total number of sales and the average sale price per car model.
With this query, the output will be a table with each row representing a different car model. The columns of the table will show the car model name, total number of sales, and average sale price.
SQL Question 5: What's the main difference between ‘BETWEEN’ and ‘IN’ operators?
The operator is used to select rows that fall within a certain range of values, while the operator is used to select rows that match values in a specified list.
For example, suppose you are a data analyst at Lithia Motors and have a table of advertising campaign data. To find campaigns with a spend between 5k, you could use BETWEEN:
To find advertising campaigns that were video and image based (as opposed to text or billboard ads), you could use the operator:
SQL Question 6: Filter Customer Vehicle Purchase Records
Consider a database with two tables - 'customers' and 'sales'. The 'customers' table tracks the customer details and the 'sales' table keeps a record of vehicle sales transactions.
The task is to write an SQL query that fetches the details of customers who have bought a 'Sports SUV' vehicle from 'Portland branch' in the year '2022'.
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 1001 | John | Doe |
| 1002 | Jane | Smith |
| 1003 | Alice | Johnson |
| 1004 | Bob | Brown |
Example Input:
| sale_id | customer_id | vehicle_type | sale_date | branch |
|---|---|---|---|---|
| 2001 | 1001 | Sports SUV | 07/15/2022 | Portland |
| 2002 | 1002 | Sedan | 06/25/2022 | Seattle |
| 2003 | 1001 | Sports Coupe | 02/12/2022 | Portland |
| 2004 | 1003 | Sports SUV | 12/18/2022 | Portland |
Answer:
This PostgreSQL query joins the 'customers' and 'sales' tables on 'customer_id'. It uses the WHERE clause to filter out the records where vehicle_type is 'Sports SUV', branch is 'Portland' and the year of the sale_date is '2022'. The EXTRACT function is used to get the year part from the 'sale_date'.
SQL Question 7: How do the and window functions differ from each other?
In SQL, both and are used to rank rows within a result set. The key difference between the two functions is how deal with two or more rows having the same value in the ranked column (aka how the break ties).
RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the second row, and a rank of 4 to the third row.
DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.
SQL Question 8: Click-Through Rate of Digital Ads for Lithia Motors
Lithia Motors routinely runs various digital ad campaigns to drive conversions to its website. The marketing team is interested in understanding the click-through rate (CTR) of these ads over a designated time period.
Assuming we have a table which records each digital advertisement impression, and a table recording every user click on these ads, you are asked to calculate the CTR for each ad during the month of August.
Example Input:
| impression_id | ad_id | date |
|---|---|---|
| 1 | 100 | 08/01/2022 |
| 2 | 100 | 08/01/2022 |
| 3 | 101 | 08/02/2022 |
| 4 | 101 | 08/02/2022 |
| 5 | 100 | 08/02/2022 |
Example Input:
| click_id | ad_id | date |
|---|---|---|
| 1 | 100 | 08/01/2022 |
| 2 | 101 | 08/02/2022 |
| 3 | 101 | 08/02/2022 |
Answer:
This PostgreSQL query calculates the CTR for each ad by dividing the number of clicks by the number of impressions. We perform a LEFT JOIN on the and tables on both and to ensure we correctly match clicks and impressions. The dates are filtered for the month of August.
To solve a similar problem about calculating rates, solve this TikTok SQL question within DataLemur's online SQL coding environment:
SQL Question 9: Analysis of Customers' Purchase History
Considering the following two tables where the 'Customers' table holds information on Lithia Motors' customers and the 'Purchases' table keeps track of vehicle purchases done by customers, write a SQL query to retrieve the number of distinct vehicle models bought by customers living in Oregon during 2020 and the total cost of these purchases.
We are interested in the results per customer and model.
Example Input:
Example Input:
Answer:
This SQL query uses a JOIN to combine data from 'Customers' and 'Purchases' tables based on the common column 'customer_id'. It then filters customers who live in Oregon and made a purchase in 2020. The query then groups records by customer information and vehicle model, outputting the number of distinct vehicle models bought (quantity) and the total cost for each group.
Because join questions come up so often during SQL interviews, try this Spotify JOIN SQL question:
Preparing For The Lithia Motors SQL Interview
The key to acing a Lithia Motors SQL interview is to practice, practice, and then practice some more!
Beyond just solving the earlier Lithia Motors SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Google, Facebook, Microsoft and Amazon.
Each problem on DataLemur has hints to guide you, step-by-step solutions and best of all, there is an online SQL coding environment so you can instantly run your SQL query answer and have it executed.
To prep for the Lithia Motors SQL interview it is also helpful to solve SQL questions from other automotive companies like:
But if your SQL query skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this SQL tutorial for Data Analytics.
This tutorial covers SQL topics like math functions in SQL and filtering data with WHERE – both of which show up routinely during SQL job interviews at Lithia Motors.
Lithia Motors Data Science Interview Tips
What Do Lithia Motors Data Science Interviews Cover?
Besides SQL interview questions, the other types of questions covered in the Lithia Motors Data Science Interview are:
- Probability & Stats Questions
- Coding Questions in Python or R
- Data Case Study Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral & Resume-Based Questions
How To Prepare for Lithia Motors Data Science Interviews?
I'm a tad biased, but I think the optimal way to prep for Lithia Motors Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book solves 201 data interview questions taken from Facebook, Google & startups. It also has a crash course on 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.