10 MaxLinear SQL Interview Questions (Updated 2024)
At MaxLinear, SQL is typically used for analyzing complex semiconductor data sets for insights, and for managing and manipulating big data in the company's large scale data infrastructure. So, it shouldn't surprise you that MaxLinear LOVES to ask SQL coding questions during interviews for Data Analytics, Data Science, and Data Engineering jobs.
So, to help you study, here's 10 MaxLinear SQL interview questions – able to answer them all?
10 MaxLinear SQL Interview Questions
SQL Question 1: Calculate Average Monthly Sales for Each Product
MaxLinear is a large multinational company that specializes in creating sophisticated semiconductors. Imagine you are a data analyst at MaxLinear, and you have been asked to analyze monthly sales data of their different product types to understand how well each product is performing.
Specifically, you are to write a SQL query that calculates the average sales volume of each product type on a monthly basis. You have been provided with the table with the following structure:
Example Input:
| sale_id | sale_date | product_id | quantity |
|---|---|---|---|
| 1 | 01/03/2022 | A | 5 |
| 2 | 15/03/2022 | B | 10 |
| 3 | 17/03/2022 | A | 15 |
| 4 | 02/04/2022 | C | 8 |
| 5 | 10/04/2022 | B | 20 |
| 6 | 20/04/2022 | A | 4 |
You are required to create a report showing the average monthly sales of each product type.
Example Output:
| month | product | avg_quantity |
|---|---|---|
| 03 | A | 10 |
| 03 | B | 10 |
| 04 | A | 4 |
| 04 | B | 20 |
| 04 | C | 8 |
Answer:
The appropriate query to solve this problem could be written like this:
In this query, we use the function to group the sales records into periods of one month. We return the and the average for each group. We used clause to group the sales data by month and product. Note that the output average quantity is rounded down to the nearest integer because SQL truncates the decimal values when giving the average of integers. If you want to return the accurate decimal average, you should cast the quantity to float in the AVG function:
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 2: 2nd Highest Salary
Suppose you had a table of MaxLinear employee salary data. Write a SQL query to find the 2nd highest salary at the company.
MaxLinear Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Try this interview question and run your code right in the browser:
Answer:
You can find a step-by-step solution here: 2nd Highest Salary.
SQL Question 3: What's the SQL command do, and when would you use it?
The SQL command merges the results of multiple statements and keeps only those rows that are present in all sets.
For example, say you were doing an HR Analytics project for MaxLinear, and had access to MaxLinear's employees and contractors data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all contractors who also show up in the employees table:
SQL Question 4: Filter MaxLinear Customers Based on Age and Purchase Frequency
As a data analyst at MaxLinear, your manager would like to get a report on the customers to focus marketing efforts. The requirements are to return a list of customers who:
- Are at least 25 years old as of now.
- Have made at least 5 purchases in the past year.
Assuming you have access to the and tables, find out the relevant customers for this task.
Example Input:
| customer_id | name | birthdate |
|---|---|---|
| 001 | John | 1985-09-12 |
| 002 | Sally | 1998-11-22 |
| 003 | Phil | 1978-05-04 |
| 004 | Linda | 1990-03-31 |
| 005 | Dave | 1995-08-23 |
Example Input:
| purchase_id | customer_id | purchase_date | amount |
|---|---|---|---|
| 1001 | 001 | 2022-07-20 | 50.00 |
| 1002 | 002 | 2022-04-10 | 30.00 |
| 1003 | 001 | 2022-05-12 | 60.00 |
| 1004 | 003 | 2022-04-08 | 80.00 |
| 1005 | 001 | 2022-01-15 | 50.00 |
| 1006 | 005 | 2022-11-22 | 30.00 |
| 1007 | 001 | 2022-08-23 | 60.00 |
| 1008 | 004 | 2022-03-20 | 100.00 |
| 1009 | 005 | 2022-06-30 | 40.00 |
| 1010 | 005 | 2022-10-15 | 30.00 |
Example Output:
| customer_id | name | born | purchase_count |
|---|---|---|---|
| 001 | John | 1985-09-12 | 4 |
Answer:
The above SQL query first joins the table with the table on the field. The where clause then adds two conditions; the first selects customers who are at least 25 years old, while the second adds a condition where purchases were made in the last year. The GROUP BY is used to consolidate all purchases by a customer. The final HAVING clause ensures we only select customers who have made at least 5 purchases in the last year.
SQL Question 5: What's the purpose of a foreign key?
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.
To demonstrate this concept, let's analyze MaxLinear's marketing analytics database which stores data from Google Ads campaigns:
:
+------------+------------+------------+------------+ | ad_id | campaign_id| keyword | click_count| +------------+------------+------------+------------+ | 1 | 100 | MaxLinear pricing | 10 | | 2 | 100 | MaxLinear reviews | 15 | | 3 | 101 | MaxLinear alternatives | 7 | | 4 | 101 | buy MaxLinear | 12 | +------------+------------+------------+------------+
is a foreign key. It references the of the Google Ads campaign that each ad belongs to, establishing a relationship between the ads and their campaigns. This foreign key allows you to easily query the table to find out which ads belong to a specific campaign, or to find out which campaigns a specific ad belongs to.
It is also possible for a table to have multiple foreign keys that reference different primary keys in other tables. For example, the table could have additional foreign keys for the of the ad group that each ad belongs to, and the of the Google Ads account that the campaigns belong to.
SQL Question 6: Calculate the Average Power Usage by Device
MaxLinear is a company dealing in semiconductor products within communication and infrastructure sectors. Assume one of their product categories is communication devices. Your task is to create a SQL query that calculates the average power usage per hour of each device in the communication devices product sector.
Example Input:
| device_id | device_name | usage_hours | power_consumed |
|---|---|---|---|
| 1 | Device A | 3 | 90 |
| 2 | Device B | 2 | 100 |
| 3 | Device C | 1 | 40 |
| 4 | Device D | 2 | 80 |
| 5 | Device E | 3 | 120 |
Example Input:
| device_id | device_name | sector |
|---|---|---|
| 1 | Device A | Communications |
| 2 | Device B | Infrastructure |
| 3 | Device C | Communications |
| 4 | Device D | Infrastructure |
| 5 | Device E | Communications |
Answer:
This query joins the 'device_power_usage' table with the 'devices' table based on the 'device_id'. It computes the average power usage per hour for each device in the 'Communications' sector. The AVG function in PostgreSQL calculates the average power consumption per hour.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for requiring calculation of total usage or this Google Odd and Even Measurements Question which is similar for involving device measurements.
SQL Question 7: What does do in a SQL query?
is used to combine the output of multiple statements into one big result!
For a concrete example, say you were doing an HR Analytics project for MaxLinear and needed to analyze both MaxLinear's employees and contractors who were hired after 2022 started. You could use in the following way:
SQL Question 8: Maximum Sales Per Region for MaxLinear
Given the table sales, find the region which has maximum sales for each product.
Consider the following tables:
Example Input:
| sale_id | sales_date | region | product_id | amount |
|---|---|---|---|---|
| 101 | 2022-06-08 | East | 1 | 500 |
| 202 | 2022-06-10 | West | 2 | 800 |
| 303 | 2022-06-18 | North | 1 | 900 |
| 404 | 2022-07-26 | East | 2 | 700 |
| 505 | 2022-07-05 | West | 1 | 600 |
Example Input:
| product_id | product_name |
|---|---|
| 1 | Product A |
| 2 | Product B |
We would like to find the region with the maximum sales for each product.
Answer:
This query works by joining the and tables using the as a common field. It then groups the rows based on the and . Finally, the function is used to find the maximum sales for each group (product and region in this case).
Expected Output:
| product_name | region | max_sales |
|---|---|---|
| Product A | East | 500 |
| Product A | North | 900 |
| Product A | West | 600 |
| Product B | East | 700 |
| Product B | West | 800 |
This result set gives us the maximum sales of each product for each region.
SQL Question 9: Filter Customers With Specific Email Domains
Suppose MaxLinear wants to run a email campaign targeted towards customers who use generic email services like gmail.com, yahoo.com, hotmail.com, etc. They have asked you to find a list of customer IDs and names who are registered with these email services. The email addresses of customers are stored in the table.
Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 6125 | John | Doe | johndoe@gmail.com |
| 7814 | Emily | Clark | emily.clark@yahoo.com |
| 5329 | Amanda | Taylor | amanda.taylor@maxlinear.com |
| 6491 | Jacob | Miller | jacob_miller@hotmail.com |
| 4578 | Sophia | Johnson | sophia.johnson@gmail.com |
We need to write SQL query to extract customer IDs and names who are registered with 'gmail.com', 'yahoo.com' and 'hotmail.com'.
Answer:
Example Output:
| customer_id | first_name | last_name |
|---|---|---|
| 6125 | John | Doe |
| 7814 | Emily | Clark |
| 6491 | Jacob | Miller |
| 4578 | Sophia | Johnson |
This SQL query uses the keyword in combination with the wildcard to match and retrieve records where the email field contains either 'gmail.com', 'yahoo.com' or 'hotmail.com'.
SQL Question 10: What's a primary key?
The primary key of a table is a column or set of columns that serves as a unique identifier for each row. It ensures that all rows are distinct and does not allow null values.
For example, say you had stored some Facebook ad campaign data that MaxLinear ran:
The CampaignID column is used to uniquely identify each row in the table, and the constraint ensures that there are no duplicate CampaignID values. This helps to maintain the accuracy of the data by preventing duplicate rows. The primary key is also an important part of the table because it enables you to easily identify and reference specific campaigns in your Facebook Ad data. You can use it to join to other tables in the database, such as a table with data on the results of the campaigns.
How To Prepare for the MaxLinear SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the MaxLinear SQL interview is to solve as many practice SQL interview questions as you can!
Beyond just solving the above MaxLinear SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each interview question has hints to guide you, detailed solutions and best of all, there's an interactive coding environment so you can instantly run your query and have it checked.
To prep for the MaxLinear SQL interview it is also helpful to solve SQL questions from other tech companies like:
In case your SQL coding skills are weak, forget about jumping right into solving questions – improve your SQL foundations with this free SQL tutorial.
This tutorial covers SQL topics like CTEs and math functions like ROUND()/CEIL() – both of these pop up often in MaxLinear SQL interviews.
MaxLinear Data Science Interview Tips
What Do MaxLinear Data Science Interviews Cover?
Besides SQL interview questions, the other question categories tested in the MaxLinear Data Science Interview include:
- Probability & Statistics Questions
- Python Pandas or R Coding Questions
- Product Analytics Questions
- ML Modelling Questions
- Resume-Based Behavioral Questions
How To Prepare for MaxLinear Data Science Interviews?
I'm sort of biased, but I think the best way to prep for MaxLinear Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book has 201 data interview questions sourced from Facebook, Google & startups. It also has a refresher on SQL, Product-Sense & ML. And finally it's helped thousands of people land their dream job in data, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.