9 Paylocity SQL Interview Questions (Updated 2024)
At Paylocity, SQL does the heavy lifting for extracting and analyzing payroll and HR data. That's why Paylocity almost always evaluates jobseekers on SQL questions in interviews for Data Science, Analytics, and & Data Engineering jobs.
So, to help you practice for the Paylocity SQL interview, we've curated 9 Paylocity SQL interview questions – can you solve them?
9 Paylocity SQL Interview Questions
SQL Question 1: Identify the Power Users from Paylocity's Transactions
Given Paylocity's customer database, in particular the transactions table, write a SQL query to identify the "whale users" - users who make the most transactions per month. The criteria for determining a whale user is subjective, but for this problem, let's say that a whale user is a user who makes more than 50 transactions a month.
Pen down a PostgreSQL query to solve the problem of finding whale users who fall under this criteria for the year 2022.
Assume you have the following table:
Example Input:
| transaction_id | user_id | transaction_date | amount |
|---|---|---|---|
| 10001 | 45 | 01/07/2022 | 450 |
| 10002 | 678 | 01/12/2022 | 200 |
| 10003 | 45 | 01/15/2022 | 120 |
| ... | ... | ... | ... |
| 10500 | 34 | 08/10/2022 | 980 |
| 10501 | 45 | 08/11/2022 | 400 |
We need to create a table that identifies users with more than 50 transactions in any given month in the year 2022.
Example Output:
| month | year | user_id | num_transactions |
|---|---|---|---|
| 1 | 2022 | 45 | 52 |
| 3 | 2022 | 678 | 57 |
| 2 | 2022 | 34 | 65 |
Answer:
In this SQL query, we are extracting the month and year from the transaction_date and then grouping by them along with the user_id. The count of transactions is computed and then we filter for those that have more than 50 transactions in a month. The result is ordered in descending order so we get the user with the highest transactions first. The EXTRACT function is specific to PostgreSQL and is used to retrieve sub-parts of a date.
To solve a similar VIP customer analysis question on DataLemur's free online SQL code editor, try this Microsoft SQL Interview problem:
SQL Question 2: Employee Performance Score Analysis
As a HR company, Paylocity provides payroll and human capital management solutions. Suppose we have an table which records the performance scores of the employees during their review cycles. Each employee gets a performance score every quarter. You are tasked to write a SQL query to find the average performance scores by quarter and the percent change in the average scores from the previous quarter, for each quarter of 2022.
Example Input:
| employee_id | review_date | score |
|---|---|---|
| 1 | 01/15/2022 | 85 |
| 2 | 01/20/2022 | 90 |
| 1 | 04/10/2022 | 88 |
| 2 | 04/15/2022 | 92 |
| 1 | 07/12/2022 | 90 |
| 2 | 07/17/2022 | 94 |
Example Output:
| quarter | avg_score | pct_change |
|---|---|---|
| 1 | 87.50 | NULL |
| 2 | 90.00 | 2.86 |
| 3 | 92.00 | 2.22 |
Answer:
Here is a PostgreSQL query that uses window functions to solve the problem:
This script first uses the function to separate the data by quarters and calculate the average score for each quarter. Then it uses the function in combination with to calculate the previous quarter's average score. The difference between the current quarter's average score and the previous quarter's average score is then divided by the previous quarter's average score to get the percent change in average scores from the previous quarter. Lastly, the function is used to handle scenarios where the denominator is zero to prevent divide-by-zero error.
To practice a similar window function question on DataLemur's free online SQL coding environment, solve this Google SQL Interview Question:
SQL Question 3: Can you describe the concept of database denormalization in layman's terms?
Database denormalization is when you add redundancy to a database, and break typical normalization rules (codified by the 1st, 2nd, 3rd normal forms).
Denormalization is typically used to improve the performance of a database, particularly when the database is being for OLAP (Online Analytical Processing) purposes. By denormalizing a database, you can reduce the number of joins that are required to retrieve data, which can greatly improve the speed of queries since joins are costly and slow. However, denormalization can also introduce some problems, such as increased data redundancy and the need for more complex update and delete operations since data has been duplicated into multiple tables.
In general, denormalization should be used with caution and only after careful consideration of the trade-offs involved. It's typically better to start with a well-normalized database design then denormalize only if your database isn't scaling as well as you want.
SQL Question 4: Analyzing Payroll Data for Employee Trends
As a part of Paylocity, a company that provides cloud-based payroll and human capital management (HCM) solutions, you are asked to analyze the monthly trends in gross salary paid to the employees. You are given two tables - and .
The table contains information about every employee like , , , etc.
The table contains data about the salaries paid to employees every month , etc.
Example Input:
Example Input:
Please write a PostgreSQL query that will output the total monthly gross salary paid to employees, the average monthly gross salary, and the total number of employees that were paid that month.
Example Output:
Answer:
This query groups by the month of the , calculates the sum of the for , calculates the average for , and counts the distinct number of 's for . These aggregate metrics are ordered by to provide a chronological overview of salary trends.
SQL Question 5: Describe the difference between UNION and UNION ALL.
The operator merges the output of two or more statements into a single result set. It ignores duplicated rows, and makes sure each row in the result set is unique.
For a concrete example, say you were a Data Analyst at Paylocity working on a Marketing Analytics project. If you needed to get the combined result set of both Paylocity's Google and Facebook ads you could execute this SQL query:
The operator works in a similar way to combine data from multiple statements, but it differs from the operator when it comes to handling duplicate rows. Whereas filters out duplicates (so if the same ad_name is run on both Facebook and Google, it only shows up once), outputs duplicate rows.
SQL Question 6: Calculate Ad Click-Through-Rates for Paylocity
You are working as a data analyst for Paylocity, a company that provides cloud-based payroll and human capital management software. The company runs various digital ads to attract potentially interested customers to its platform. You are tasked to analyze the efficiency of these ads by calculating the click-through-rate, which is the ratio of users who click on a specific link to the number of total users who view the advertisement.
Given two tables, and , calculate the click-through-rate for each ad for the month of October 2022.
Example Input:
| ad_id | display_date |
|---|---|
| 101 | 10/02/2022 00:00:00 |
| 102 | 10/05/2022 00:00:00 |
| 103 | 10/10/2022 00:00:00 |
| 104 | 10/15/2022 00:00:00 |
| 105 | 10/20/2022 00:00:00 |
Example Input:
| click_id | ad_id | click_date |
|---|---|---|
| 501 | 101 | 10/03/2022 00:00:00 |
| 502 | 102 | 10/06/2022 00:00:00 |
| 503 | 102 | 10/06/2022 00:00:00 |
| 504 | 103 | 10/11/2022 00:00:00 |
| 505 | 104 | 10/15/2022 00:00:00 |
Answer:
The PostgreSQL query to solve this problem would be as follows:
This query firstly selects and calculates the total number of clicks for each ad using . It generates the click-through-rate by dividing each ad's total clicks by the total number of displayed ads in October 2022. The ads are listed from highest to lowest click-through-rate.
To solve a related SQL problem on DataLemur's free interactive SQL code editor, attempt this SQL interview question asked by Facebook:
SQL Question 7: In database design, what do foreign keys do?
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 Paylocity's marketing analytics database which stores data from Google Ads campaigns:
:
+------------+------------+------------+------------+ | ad_id | campaign_id| keyword | click_count| +------------+------------+------------+------------+ | 1 | 100 | Paylocity pricing | 10 | | 2 | 100 | Paylocity reviews | 15 | | 3 | 101 | Paylocity alternatives | 7 | | 4 | 101 | buy Paylocity | 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 8: Analyzing Paylocity Customers and Transactions
As a data analyst at Paylocity, your manager would like to analyze the company's customer base, specifically the average transaction amount by customer's age segment. For this analysis, you have two tables, and .
The table has following columns:
- : Unique Customer Identification Number
- : Customer's Name
- : Customer's Date of Birth
The table has the following columns:
- : Unique Transaction Identification Number
- : Customer Identification Number (links to ID field in Customers Table)
- : Amount of the transaction
Generate a SQL query that will summarize the average transaction amount per each age group:
- 18-25
- 26-35
- 36-45
- 46-55
- Above 55
Example Input:
| ID | Name | DOB |
|---|---|---|
| 1 | John Smith | 1994-07-07 |
| 2 | Eric Johnson | 1985-05-14 |
| 3 | Paul Brown | 1975-10-18 |
| 4 | Karen Davis | 1998-12-01 |
| 5 | Tina Williams | 1963-11-21 |
Input Example:
| Transaction_ID | Customer_ID | Transaction_Amount |
|---|---|---|
| 1 | 1 | 100 |
| 2 | 2 | 300 |
| 3 | 3 | 150 |
| 4 | 2 | 200 |
| 5 | 4 | 250 |
| 6 | 5 | 175 |
| 7 | 1 | 225 |
| 8 | 4 | 125 |
| 9 | 3 | 325 |
| 10 | 5 | 50 |
Answer:
In this answer, we've joined and using customer ID. Then, with the use of the function, customers are divided into age segments. These segments are then used to group the data, and for each group, the function is applied to the column to calculate the average transaction amount.
Since joins come up so often during SQL interviews, try this interactive Snapchat JOIN SQL interview question:
SQL Question 9: Employee performance based on tasks
At Paylocity, managers need to rank employee performance based on the number of tasks completed, average task completion time, and the error rate in task completion.
Use a common scale of 0-100 to calculate these performance metrics where for the number of tasks more is better, for average task completion time less is better, and for the error rate the lower the better.
Assume the tasks are the same for everyone and there are no undefined values in the tables.
Table Input:
| employee_id | first_name | last_name |
|---|---|---|
| 23 | John | Doe |
| 31 | Jane | Smith |
| 45 | Alex | Ball |
| 52 | Tina | Wright |
| 67 | Sam | Black |
Table Input:
| task_id | employee_id | completion_time_hours | errors |
|---|---|---|---|
| 1 | 23 | 2 | 0 |
| 2 | 23 | 3 | 1 |
| 3 | 31 | 5 | 0 |
| 4 | 45 | 2 | 0 |
| 5 | 45 | 2 | 0 |
| 6 | 52 | 4 | 2 |
| 7 | 67 | 3 | 1 |
| 8 | 31 | 1 | 0 |
| 9 | 45 | 4 | 1 |
| 10 | 67 | 2 | 0 |
Answer:
This query first aggregates the tasks table to get the needed performance metrics for each employee in task_data. The max_min table then gathers the maximum and minimum values for scaling later. The final query brings everything together, calculating the scaled scores by subtracting the minimum from the value, dividing by the range, and multiplying by 100 for a 0-100 scale for employee performance.
To practice a very similar question try this interactive Microsoft Teams Power Users Question which is similar for performance ranking based on metrics or this Facebook Advertiser Status Question which is similar for calculating metrics using conditionals.
How To Prepare for the Paylocity SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Paylocity SQL interview is to solve as many practice SQL interview questions as you can!
Beyond just solving the above Paylocity SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Google, Uber, and Microsoft.
Each problem on DataLemur has multiple hints, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an interactive coding environment so you can right in the browser run your SQL query and have it checked.
To prep for the Paylocity SQL interview you can also be useful to solve SQL questions from other tech companies like:
In case your SQL foundations are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.
This tutorial covers topics including Self-Joins and handling NULLs in SQL – both of which show up often in Paylocity SQL interviews.
Paylocity Data Science Interview Tips
What Do Paylocity Data Science Interviews Cover?
In addition to SQL query questions, the other types of questions tested in the Paylocity Data Science Interview are:
- Statistics and Probability Questions
- Python or R Coding Questions
- Product Data Science Interview Questions
- ML Modelling Questions
- Behavioral & Resume-Based Questions
How To Prepare for Paylocity Data Science Interviews?
To prepare for Paylocity Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG, tech startups, and Wall Street
- a refresher covering SQL, Product-Sense & ML
- over 900+ 5-star reviews on Amazon