9 TriNet SQL Interview Questions (Updated 2025)

TriNet employees write SQL queries for analyzing HR data, including employee demographics and benefits utilization, to inform business decisions. They also use it for managing their extensive employee databases to update employee information and track benefits enrollment, for optimization and efficient data retrieval, which is why TriNet asks SQL questions in interviews for Data Science and Data Engineering positions.

So, to help you study, here’s 9 TriNet Group SQL interview questions – can you answer each one?

9 TriNet Group SQL Interview Questions

SQL Question 1: Identifying Power Users from TriNet's Services Usage Data

TriNet is a company that provides full-service HR solutions for small and medium size businesses. They offer services such as payroll processing, benefit plans administration, risk mitigation and compliance, and much more. A power user in TriNet's context could be considered as a company that uses multiple services very frequently.

Your task is to write a SQL query to identify the top 5 companies (based on company_id) who use the highest number of different services monthly.

Below are the sample input and output tables:

service_usage Example Input:

Example Output:

Answer:

SELECT 
    EXTRACT(MONTH FROM usage_date) as month, 
    company_id,
    COUNT(DISTINCT service_id) as different_services_used_count
FROM 
    service_usage 
GROUP BY 
    month, 
    company_id 
ORDER BY 
    different_services_used_count DESC LIMIT 5;

This SQL command works by grouping records by month and company_id, and generates the count of unique services used. The records are ordered by the count of services (in descending order) and it returns the top 5 records. This information then can be used to analyze and target power users.

To practice a super-customer analysis question on DataLemur's free interactive SQL code editor, try this Microsoft SQL Interview problem:

SQL Question 2: Second Highest Salary

Given a table of TriNet employee salaries, write a SQL query to find the 2nd highest salary at the company.

TriNet employees Example Input:

Example Output:

You can solve this question directly within the browser on DataLemur:

Answer:

SELECT MAX(salary) AS second_highest_salary
FROM employee
WHERE salary < (
    SELECT MAX(salary)
    FROM employee
);

You can find a step-by-step solution with hints here: 2nd Highest Salary.

SQL Question 3: What's database denormalization?

Denormalization is a technique used to improve the read performance of a database, typically at the expense of some write performance.

By adding redundant copies of data or grouping data together in a way that does not follow normalization rules, denormalization improves the performance and scalability of a database by eliminating costly join operations, which is important for OLAP use cases that are read-heavy and have minimal updates/inserts.

SQL Question 4: Calculate Average Salary by Department for Each Month using Window Functions

You are a data analyst for TriNet. You're given a table named salaries, which keeps a log of employee salaries. Each record in the table represents a log entry – when an employee's salary was changed, a new record was inserted.

The schemas for the salaries table is shown below:

salaries Example Input:

The department_id maps to a department_name in the departments table:

departments table:

Your task is to write an SQL query that will return the average salary for each department for each month present in the salaries table. Consider the most recent salary of an employee for a given month.

Answer:

WITH monthly_salaries AS (
  SELECT employee_id, 
         department_id, 
         salary,
         DATE_TRUNC('month', date_changed) AS month,
         ROW_NUMBER() OVER(
           PARTITION BY employee_id, DATE_TRUNC('month', date_changed)
           ORDER BY date_changed DESC
         ) AS rn
  FROM salaries
)

SELECT DATE_TRUNC('month', month) AS month,
       d.department_name,
       ROUND(AVG(salary), 2) AS avg_salary
FROM monthly_salaries ms
JOIN departments d ON ms.department_id = d.department_id
WHERE ms.rn = 1
GROUP BY DATE_TRUNC('month', month), d.department_name
ORDER BY month, avg_salary DESC;

In this SQL statement, we first create a Common Table Expression (CTE) that partitions the data by the employee ID and the month of the salary change, ordering by the date of salary change in descending order. This allows us to tag the most recent salary change for each employee in a given month.

Then, we select the month, department name, and calculate the average salary from the CTE where the row number is 1 (most recent salary change within the month), joining with the departments table to get the department names. We group by the month and the department name to give the average salary for each department per month. We order the output by month and average salary in descending order to make the result set easier to understand.

To solve a similar window function question on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:

SQL Question 5: In SQL, are blank spaces the same as a NULL?

In SQL, a NULL 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 COALESCE() function is often used to check for a null, and if there is a null, you can assign a default value.

SQL Question 6: Calculate the Average Employee Salary for Each Department

TriNet is a company providing full-service HR solutions for small and midsize businesses. For this context, suppose you are given a task to find the average salary of each department in TriNet. You are provided with two tables - 'employees' and 'departments'. The 'employees' table has the 'employee_id', 'department_id' and 'salary'. The 'departments' table has the 'department_id' and 'department_name'.

employees Example Input:

departments Example Input:

Example Output:

Answer:

SELECT d.department_name, AVG(e.salary)
FROM employees e
JOIN departments d ON e.department_id = d.department_id
GROUP BY d.department_name;

In the above query, we first join the 'employees' and 'departments' tables based on 'department_id'. Then we group by 'department_name' and calculate the average salary for each group. The AVG function calculates the average of a set of values. The result is the average salary for each department.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for grouping and summarizing data or this Facebook Advertiser Status Question which is similar for handling company data.

SQL Question 7: Can you explain the distinction between cross join and natural join?

A cross join is a type of JOIN operation in SQL that creates a new table by combining each row from the first table with every row from the second table. It is also known as a cartesian join.

For example, say you worked on the Marketing Analytics team at TriNet, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).

Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:

SELECT ad_copy.copy AS ad_copy, ad_creative.image_url AS ad_creative
FROM ad_copy
CROSS JOIN ad_creative;

A natural join, on the other hand, is a type of JOIN that combines rows from two or more tables based on their common columns. It is called a "natural" join because it is based on the natural relationship that exists between the common columns in the tables being joined.

For an example of each one, say you had sales data exported from TriNet's Salesforce CRM stored in a datawarehouse which had two tables: sales and trinet_customers.

An INNER JOIN (which is a type of natural join) combines the two tables on the common customer_id field

SELECT *
FROM sales
INNER JOIN trinet_customers
ON sales.customer_id = trinet_customers.id

This query will return rows from the sales and trinet_customers tables that have matching customer id values. Only rows with matching customer_id values will be included in the results.

One main difference between cross joins and natural joins is that cross joins do not require any common columns between the tables being joined, while natural joins do. Another difference is that cross joins can create very large tables if the input tables have a large number of rows, while natural joins will only return a table with the number of rows equal to the number of matching rows in the input tables.

SQL Question 8: Find the Average Client Satisfaction

As a data analyst at TriNet, a company providing HR solutions especially for small and midsize businesses, you are tasked to gauge client satisfaction. Specifically, your manager wants to know the average client review score for each offered HR service per month. Can you write a SQL query to obtain this data?

Let's consider a table client_reviews which captures client's reviews (scored out of 5) for the different services TriNet offers.

client_reviews Example Input:

We would like an output like this, which provides the average review score grouped by month and service:

Example Output:

Answer:

SELECT
    EXTRACT(MONTH FROM submit_date) as month,
    service_id,
    AVG(review_score) as avg_review_score
FROM
    client_reviews
GROUP BY
    month,
    service_id
ORDER BY
    month,
    service_id;

This query functions by using the EXTRACT function to get the month from the submit_date field. It then groups the output by this calculated month, and the service_id in the GROUP BY clause. The AVG function is used to calculate the mean review score for each pair of (month, service_id). Lastly, the result is ordered by month and service_id.

SQL Question 9: Joining and Analyzing Customer and Order Data

You are given two tables; one contains the customer details (customer_info) and another contains their order details (customer_orders). Your task is to write a SQL query to analyze the customer database and join that with the order table to find the total spending of each customer.

Here are the tables for the provided dataset:

customer_info Example Input:

customer_orders Example Input:

Answer:

Here is the SQL block to find the total spending by each customer:

SELECT ci.first_name, ci.last_name, SUM(co.total_price) as total_spending
FROM customer_info ci
LEFT JOIN customer_orders co ON ci.customer_id = co.customer_id
GROUP BY ci.first_name, ci.last_name
ORDER BY total_spending DESC;

In this query, we are joining customer_info with customer_orders on customer_id to retrieve all orders made by each customer. We then group the joined tables by each customer and calculate their total spendings. The SUM function is used to add up the total_price of all orders for each customer, and GROUP BY is used to group the results per customer. Finally, the ORDER BY clause sorts the customers by their total spending in descending order.

Because join questions come up frequently during SQL interviews, try an interactive SQL join question from Spotify:

TriNet SQL Interview Tips

The best way to prepare for a TriNet SQL interview is to practice, practice, practice. Besides solving the above TriNet SQL interview questions, you should also solve the 200+ tricky sql questions 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 is an interactive coding environment so you can right online code up your query and have it graded.

To prep for the TriNet SQL interview it is also wise to solve interview questions from other enterprise software companies like:

• Salesforce SQL questions
• Oracle SQL questions
• Salesforce SQL questions
• ADP SQL questions

Discover how leveraging AI streamlines business operations with Trinet's latest article!

In case your SQL query skills are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this free SQL tutorial.

This tutorial covers topics including Union vs. UNION ALL and LEAD window function – both of these pop up routinely during SQL interviews at TriNet.

TriNet Group Data Science Interview Tips

What Do TriNet Data Science Interviews Cover?

In addition to SQL query questions, the other question categories to prepare for the TriNet Data Science Interview are:

• Stats Interview Questions
• Python Pandas or R Coding Questions
• Product-Sense Questions
• ML Interview Questions
• Behavioral Interview Questions

How To Prepare for TriNet Data Science Interviews?

To prepare for the TriNet Data Science interview make sure you have a strong understanding of the company's values and mission – this will be important for acing the behavioral interview. For technical interviews prepare by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from Facebook, Google & startups
• A Crash Course on SQL, AB Testing & ML
• Amazing Reviews (1000+ 5-star reviews on Amazon)