8 Paycom SQL Interview Questions (Updated 2024)
At Paycom, SQL crucial for analyzing payroll and human capital management data. That's why Paycom typically asks SQL interview questions during technical interviews for Data Science, Data Engineering and Data Analytics jobs.
As such, to help you prepare for the Paycom SQL interview, we've collected 8 Paycom SQL interview questions – able to answer them all?
8 Paycom SQL Interview Questions
SQL Question 1: Identify the most frequent payroll processors through Paycom
Paycom is a reputable provider of comprehensive, cloud-based Human Capital Management (HCM) software. Important users in this scenario may be those who process payroll most frequently, as this is a key activity in Human Capital Management software.
Table 1:
| user_id | username | signup_date |
|---|---|---|
| 1001 | JohnDoe | 2020-01-01 |
| 1002 | JaneDoe | 2020-01-02 |
| 1003 | Alice | 2020-01-03 |
Table 2:
| payroll_id | user_id | processing_date |
|---|---|---|
| 5001 | 1001 | 2022-07-01 |
| 5002 | 1001 | 2022-07-15 |
| 5003 | 1002 | 2022-07-10 |
| 5004 | 1001 | 2022-08-01 |
| 5005 | 1003 | 2022-08-05 |
| 5006 | 1001 | 2022-08-15 |
For this question, you are to write a SQL query to identify the top 3 users who processed payroll the most in the last 3 months. Additionally, return the number of times they processed payroll during this period.
Answer:
This solution operates by joining the table with the table on the field, subsequently filtering for payrolls processed in the last 3 months. It then groups the payrolls processed by username and orders them in descending order. The limit clause is used to restrict the output to the top 3 users who processed payroll the most.
To work on another SQL customer analytics question where you can solve it right in the browser and have your SQL code automatically checked, try this Walmart Labs SQL Interview Question:
SQL Question 2: Average Employee Salary Calculation
As an HR Tech company, Paycom manages a lot of employee data. One type of analysis that is often carried out involves comparing salaries across departments in the company. The question is to find out the average salary per department, and calculate how each employee's salary differs from the average of their respective department. For this exercise, assuming we have an "employees" table containing the pertinent data.
Example Input:
| id | name | department | salary |
|---|---|---|---|
| 1 | John | Engineering | 70000 |
| 2 | Jane | Sales | 80000 |
| 3 | Doe | Engineering | 60000 |
| 4 | Smith | Sales | 90000 |
| 5 | Mike | Engineering | 75000 |
We want to get each employee's salary, and the average salary of their respective department, and the difference between the two.
Example Output:
| id | name | department | salary | average_salary | difference |
|---|---|---|---|---|---|
| 1 | John | Engineering | 70000 | 68333.33 | 1666.67 |
| 2 | Jane | Sales | 80000 | 85000 | -5000 |
| 3 | Doe | Engineering | 60000 | 68333.33 | -8333.33 |
| 4 | Smith | Sales | 90000 | 85000 | 5000 |
| 5 | Mike | Engineering | 75000 | 68333.33 | 6666.67 |
Answer:
This query starts by selecting the columns we are interested in from the "employees" table. The magic happens in the section, where we calculate the average salary for each department (by using PARTITION BY). We then subtract this average from the individual salary to find the difference. Window functions like AVG() OVER () allow you to perform calculations across sets of rows that are related to the current row, which is why you're able to do this all in one pass, rather than having to do separate queries for each department's average.
To practice a related window function SQL problem on DataLemur's free online SQL code editor, solve this Amazon SQL Interview Question:
SQL Question 3: What's the SQL command do, and can you give an example?
If you have two tables and want to retrieve only the rows that are present in both tables, just use the operator!
For example, let's use to find all of Paycom's Facebook video ads that are also being run on YouTube:
SQL Question 4: Find Average Payroll Processed per Client
Suppose Paycom wishes to understand more about the average payroll processed per client each month to better manage its resources. The task is to write an SQL query, which finds the monthly average amount of payroll processed for each client.
Let us consider a table that captures the client_id, total_compensation (amount of payroll), and the date when the payroll is processed:
Example Input:
| payroll_id | client_id | process_date | total_compensation |
|---|---|---|---|
| 5121 | 432 | 01/11/2022 | 75000 |
| 1332 | 432 | 02/08/2022 | 78000 |
| 8294 | 762 | 01/19/2022 | 50000 |
| 3321 | 875 | 01/20/2022 | 120000 |
| 1419 | 432 | 03/10/2022 | 76000 |
- is a unique identifier for each payroll processed.
- indicates the Paycom client who processed the payroll.
- is the date when the payroll was processed.
- is the total amount of the payroll.
The output should provide the month, the client, and the average amount of payroll processed in the respective month, sorted by month in ascending order.
Example Output:
| mth | client | avg_payroll |
|---|---|---|
| 1 | 432 | 75000 |
| 1 | 762 | 50000 |
| 1 | 875 | 120000 |
| 2 | 432 | 78000 |
| 3 | 432 | 76000 |
Answer:
In this query, we use PostgreSQL’s DATE_PART function to pull out the month part of the process_date. We then group by both the month and client_id to compute the average payroll processed per client each month. We also cast the average payroll value to be a numeric type with two decimal places for better readability. The result is ordered by the month in ascending order. This provides a monthly understanding of the average payroll amount processed by each client.
SQL Question 5: What's a foreign key?
A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables. The table with the foreign key is called the child table, while the table with the candidate key is called the parent or referenced table.
For example, consider a database with two tables: and customer_idcustomer_idcustomer_id` column in Paycom customers table.
SQL Question 6: Analyze Customer Purchase Behavior
In Paycom, we have two main tables: a table that tracks basic customer information, and a table that records all purchase transactions. The task is to write a SQL query to join these two tables, and find the total amount spent by each customer and the number of unique items they have purchased. This analysis would help Paycom to understand individual customer's purchase behavior.
Here are some sample tables for this problem:
Example Input:
| customer_id | name | date_joined |
|---|---|---|
| 111 | John | 2019-07-02 |
| 222 | Sara | 2021-01-13 |
| 333 | Dave | 2018-11-27 |
Example Input:
| purchase_id | customer_id | item_id | purchase_amount | purchase_date |
|---|---|---|---|---|
| 1 | 111 | A1 | 50 | 2021-10-01 |
| 2 | 222 | A2 | 100 | 2021-10-01 |
| 3 | 111 | A1 | 50 | 2021-10-02 |
| 4 | 222 | A3 | 150 | 2021-10-03 |
| 5 | 333 | A1 | 50 | 2021-10-03 |
Answer:
This query first joins the and tables using the column. Then it groups the data by and , and for each group, it calculates the total purchase amount and counts the number of distinct item IDs. This gives us the total amount spent by each customer and the number of unique items they have purchased. The result is then ordered by in descending order.
Since joins come up frequently during SQL interviews, try an interactive SQL join question from Spotify:
SQL Question 7: In the context of databases, what does atomicity, consistency, isolation, and durability mean?
A DBMS (database management system), in order to ensure transactions are relaible and don't ruin the integrity of the data, tries to mantain the following ACID properties: Atomicity, Consistency, Isolation, and Durability.
To make this concept more concrete, here is what each of the ACID properties would mean in the context of banking transactions:
- Atomicity: a transaction is either completed fully, or not complete at all. For example, if a customer is transferring money from one account to another, the transaction should either transfer the full amount or none at all.
- Consistency: a transaction will only be completed if it follows all database constraints and checks. For example, if a customer is withdrawing money from an account, the transaction should only be completed if the account has sufficient funds available, otherwise the transaction is rejected
- Isolation: ensures that concurrent transactions are isolated from each other, so that the changes made by one transaction cannot be seen by another transaction. This isolation prevents race conditions, like two customers trying to withdraw money from the same account at the same time.
- Durability: ensures that once a transaction has been committed and completed, the changes are permanent. A reset / shutdown of the database shouldn't erase someone's savings accounts!
SQL Question 8: Average Processing Time Per Month
Given the Paycom is a human resources technology provider company, let's assume you are provided with 2 tables. The first table called has information about all the employees working in the company. The second table has information about when the payroll of each employee was processed in each month.
Write a SQL query to find the average number of days it takes to process payroll for each month. The result should be sorted in ascending order of the month number.
Example Input:
| employee_id | first_name | last_name | dept_id |
|---|---|---|---|
| 1 | John | Doe | 100 |
| 2 | Jane | Doe | 200 |
| 3 | Ramesh | Kumar | 300 |
| 4 | Yang | Li | 300 |
| 5 | Maria | Gonzalez | 100 |
Example Input:
| payroll_id | employee_id | process_start_date | process_complete_date |
|---|---|---|---|
| 1 | 1 | 2022-01-01 | 2022-01-03 |
| 2 | 2 | 2022-01-02 | 2022-01-04 |
| 3 | 3 | 2022-01-01 | 2022-01-01 |
| 4 | 4 | 2022-02-02 | 2022-02-10 |
| 5 | 5 | 2022-02-01 | 2022-02-03 |
Example Output:
| month | average_processing_time |
|---|---|
| 1 | 2.00 |
| 2 | 5.00 |
Answer:
This query works by first extracting the month from every process start date. Then the difference in days between the process complete date and process start date is calculated. The average function is used to get the average processing time. The result is sorted by month number in ascending order.
Paycom SQL Interview Tips
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews.
Besides solving the earlier Paycom SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Uber, and Microsoft.
Each exercise has multiple hints, full answers and best of all, there is an online SQL coding environment so you can right in the browser run your SQL query and have it executed.
To prep for the Paycom SQL interview you can also be a great idea to solve interview questions from other tech companies like:
But if your SQL skills are weak, forget about jumping right into solving questions – strengthen your SQL foundations with this free SQL tutorial.
This tutorial covers SQL topics like aggreage functions like MIN()/MAX() and aggregate window functions – both of which come up routinely during Paycom interviews.
Paycom Data Science Interview Tips
What Do Paycom Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories tested in the Paycom Data Science Interview are:
- Probability & Stats Questions
- Coding Questions in Python or R
- Product-Sense and Business Case Questions
- ML Modelling Questions
- Resume-Based Behavioral Questions
How To Prepare for Paycom Data Science Interviews?
To prepare for Paycom Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Facebook, Google, & Amazon
- a refresher covering Python, SQL & ML
- over 900+ 5-star reviews on Amazon