Data Scientists, Analysts, and Data Engineers at Lear write SQL queries for analyzing manufacturing data for efficiency improvements, and conducting predictive analysis on component durability. Because of this, Lear frequently asks jobseekers SQL coding interview questions.
To help you prepare for the Lear SQL interview, we'll cover 10 Lear SQL interview questions can you solve them?
You work for the Lear company, which is an e-commerce platform. After digesting business requirements, you've discovered that the products team would like to analyze product ratings over time to better understand which products are receiving high and low ratings.
You have been given access to the "reviews" table, which contains product reviews, each with a unique ID, the ID of the user who submitted the review, the date the review was submitted, the ID of the product being reviewed, and the number of stars given to the product (1 to 5).
Please write a SQL query that calculates the average star rating by product on a monthly basis.
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 |
month | product_id | avg_stars |
---|---|---|
6 | 50001 | 3.50 |
6 | 69852 | 4.00 |
7 | 69852 | 2.50 |
This query starts by extracting the month from the submit_date field, which is then used in combination with product_id in the GROUP BY clause. This ensures that the average star rating is calculated for each product in each month. The ORDER BY clause orders the output first by month and then by product_id.
Pro Tip: Window functions are a frequent SQL interview topic, so practice every window function problem on DataLemur
Given a table of Lear employee salaries, write a SQL query to find the 2nd highest salary amongst all the employees.
employee_id | salary |
---|---|
1 | 2500 |
2 | 800 |
3 | 1000 |
4 | 1200 |
second_highest_salary |
---|
1200 |
Write a SQL query for this problem directly within the browser on DataLemur:
You can find a detailed solution here: 2nd Highest Salary.
A non-relational (NoSQL) database is any database that does not use the typical tabular format of rows and columns like in relational databases.
While knowing the four different types of NoSQL databases is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at Lear should vaguely refresh these concepts:
Lear is an automotive technology company that regularly runs marketing campaigns to promote its products. As a Data Analyst at Lear, you are asked to calculate the Click-Through-Rate (CTR) of each advertising campaign. The CTR is a common marketing metric that measures the number of clicks advertisers receive on their ads per the number of impressions (ad views).
Lear's and data are stored in the following tables:
campaign_id | product_id | start_date | end_date |
---|---|---|---|
101 | A1 | 01/01/2022 | 01/31/2022 |
102 | B1 | 02/01/2022 | 02/28/2022 |
103 | C1 | 03/01/2022 | 03/31/2022 |
104 | A1 | 04/01/2022 | 04/30/2022 |
click_id | campaign_id | click_date |
---|---|---|
201 | 101 | 01/15/2022 |
202 | 101 | 01/18/2022 |
203 | 102 | 02/11/2022 |
204 | 103 | 03/25/2022 |
205 | 104 | 04/03/2022 |
206 | 104 | 04/05/2022 |
The table contains information about each of Lear's marketing campaigns, including the campaign ids, the product ids that are being promoted ("A1", "B1", "C1"), and the start and end dates of the campaigns.
The table contains information about the clicks that each campaign received, including the click ids, the corresponding campaign ids, and the dates when the clicks occurred.
In PostgreSQL, we can calculate the CTR of each campaign by first counting the number of clicks each campaign received and then dividing this count by the number of impressions (ad views). However, the number of impressions data is not given. For the purposes of this example, let's say each campaign had 1000 impressions.
Here's a SQL query that can be used to calculate the CTR for each campaign:
This query first joins the campaigns and clicks tables on the campaign_id column. It then calculates the total number of clicks each campaign received (total_clicks) and divides this by the number of impressions (1000 in this case) to compute the CTR. The results are sorted in descending order of CTR.
To solve a related SQL interview question on DataLemur's free interactive coding environment, try this SQL interview question asked by Facebook:
The UNION operator combines the results from multiple SELECT statements into a single result set.
Here's an example of using the UNION operator to combine the results of two SELECT statements that retrieve data from tables of Lear's Facebook ads and their Google ads:
This statement would return a combined result set of both Facebook and Google ads that have a spend greater than $200. The result set would include the following columns: ad_id, ad_name, ad_type, impressions, clicks, and spend.
Note that the two SELECT statements within the UNION must have the same number of columns and the columns must have similar data types. In this example, both SELECT statements have the same number of columns and the data types of the columns are all compatible.
As an analyst at Lear Corporation, an international car parts supplier, your task is to monitor the sales performance of the different automobile parts supplied by the company. You are specifically interested in getting the monthly sales total for each product. You are provided with the sales table where every row represents a sale. Note that every sale is automatically recorded at the time of the transaction.
sale_id | sale_date | product_id | qty | price |
---|---|---|---|---|
6124 | 03/01/2022 12:00:00 | 105 | 10 | 500 |
7805 | 03/15/2022 15:00:00 | 185 | 8 | 800 |
5272 | 04/18/2022 16:00:00 | 105 | 15 | 500 |
6336 | 04/26/2022 10:00:00 | 185 | 20 | 800 |
4505 | 05/05/2022 13:00:00 | 255 | 25 | 400 |
The table contains the following columns:
Write a query to determine the total sales for each product for each month, sorted by month and product ID.
mth | product | total_sales |
---|---|---|
3 | 105 | 5000 |
3 | 185 | 6400 |
4 | 105 | 7500 |
4 | 185 | 16000 |
5 | 255 | 10000 |
This query first selects the month from the column and the column. It then calculates the total sales by multiplying and for each product per month. The clause groups the results by month and product. Lastly, the clause sorts the result by month and product id.
Fun Fact: Lear was recognized as a top employer in Europe in 2024!!
A database view is a virtual table that is created based on the results of a SELECT statement, and provides you a customized, read-only version of your data that you can query just like a regular table.
You'd want to use a view for a few reasons:
As part of data cleanup, your task is to find all users from the company's database who have emails registered under the domain "@lear.com". Also, you should retrieve their full names and user IDs.
Assuming you have the following User Data:
user_id | first_name | last_name | |
---|---|---|---|
001 | John | Doe | john.doe@lear.com |
002 | Jane | Smith | jane.smith@google.com |
003 | Paul | Jones | paul.jones@lear.com |
004 | Emily | Brown | emily.brown@yahoo.com |
005 | Michael | Davis | michael.davis@lear.com |
To solve this problem, we could use the keyword in the clause in our SQL query to filter out the users with emails that end in "@lear.com". The SQL query would look like this:
This SQL query will return a result of all users who have their email registered with the "@lear.com" domain along with their user IDs and full names.
We have a company named Lear, which maintains a database with tables and .
The table contains the data regarding each customer's purchases, their names, and the company they work for. The table contains the data about the company name and its address.
You are tasked to write a SQL query to join these two tables and provide a list showing each customer's name, their average purchase amount, and their employer's name and address.
customer_id | name | employer_id | purchase_amount |
---|---|---|---|
1 | John Doe | 101 | 1200 |
2 | Jane Smith | 102 | 800 |
3 | Alice Johnson | 101 | 1600 |
4 | Bob Williams | 103 | 1000 |
5 | Charlie Brown | 102 | 1400 |
employer_id | company | address |
---|---|---|
101 | Microsoft | Redmond, WA |
102 | Amazon | Seattle, WA |
103 | Mountain View, CA |
Here's a PostgreSQL query which can get the desired results:
This SQL statement uses the INNER JOIN clause to combine rows from the and tables. The AVG() function is used with the OVER() clause to calculate the average purchase amount for each unique employer_id in the table. The result is a list of customers with their average purchase amount and their employer details.
Since join questions come up frequently during SQL interviews, practice this interactive Snapchat SQL Interview question using JOINS:
{#Question-10}
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.
The best way to prepare for a Lear SQL interview is to practice, practice, practice. Besides solving the earlier Lear SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like Microsoft, Google, and Facebook.
Each interview question has hints to guide you, full answers and best of all, there is an online SQL coding environment so you can instantly run your query and have it checked.
To prep for the Lear SQL interview you can also be helpful to practice SQL questions from other automotive companies like:
However, if your SQL skills are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this interactive SQL tutorial.
This tutorial covers SQL concepts such as how window functions work and rank window functions – both of these come up often during SQL interviews at Lear.
In addition to SQL interview questions, the other topics to prepare for the Lear Data Science Interview are:
To prepare for Lear Data Science interviews read the book Ace the Data Science Interview because it's got: