8 Alight Solutions SQL Interview Questions (Updated 2024)
At Alight, SQL is used across the company for extracting and manipulating employee benefits data, and to generate insights for human resource leaders. That's why Alight Solutions LOVES to ask SQL query questions in interviews for Data Analytics, Data Science, and Data Engineering jobs.
Thus, to help you practice for the Alight Solutions SQL interview, this blog covers 8 Alight SQL interview questions – can you solve them?
8 Alight SQL Interview Questions
SQL Question 1: Analyze Employee Performance
As an HR analytics firm, Alight Solutions has to deal with a lot of employee data. Suppose, we have data of employees' performance throughout a year. We want to find out the average performance rating, maximum and minimum performance rating of each employee from the previous quarter. Create a SQL query to solve this problem using a Window Function.
Example Input:
| transaction_id | employee_id | quarter | year | performance_rating |
|---|---|---|---|---|
| 1 | 001 | 1 | 2022 | 3.5 |
| 2 | 001 | 2 | 2022 | 3.7 |
| 3 | 002 | 3 | 2022 | 4.1 |
| 4 | 001 | 3 | 2022 | 3.8 |
| 5 | 002 | 4 | 2022 | 4.3 |
| 6 | 003 | 1 | 2022 | 4.0 |
| 7 | 002 | 2 | 2022 | 3.9 |
| 8 | 003 | 3 | 2022 | 3.7 |
| 9 | 003 | 4 | 2022 | 4.0 |
Example Output:
| year | quarter | employee_id | avg_performance_rating | max_performance_rating | min_performance_rating |
|---|---|---|---|---|---|
| 2022 | 2 | 001 | 3.6 | 3.7 | 3.5 |
| 2022 | 3 | 001 | 3.7 | 3.8 | 3.5 |
| 2022 | 4 | 001 | 3.66 | 3.8 | 3.5 |
| 2022 | 2 | 002 | 4.1 | 4.1 | 4.1 |
| 2022 | 3 | 002 | 4.0 | 4.1 | 3.9 |
| 2022 | 4 | 002 | 4.1 | 4.3 | 3.9 |
| 2022 | 2 | 003 | 4.0 | 4.0 | 4.0 |
| 2022 | 3 | 003 | 3.85 | 4.0 | 3.7 |
| 2022 | 4 | 003 | 3.9 | 4.0 | 3.7 |
Answer:
This SQL query uses PostgreSQL's window functions. Here, the , and functions work over a window of rows partitioned by and ordered by . ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING specifies that the window will start from the first row of the partition to the one before the current row, thus enabling analysis of the employee's past performance up to the current quarter.
Pro Tip: Window functions are a popular SQL interview topic, so practice every window function problem on DataLemur
SQL Question 2: Calculate the Average Salary for Each Job Role
As an HR Analyst at Alight Solutions, you've been asked to analyze the employee salary distribution across various job roles in the company. Alight Solutions is known for its HR and financial solutions, and this analysis would help them better understand how the average salary varies from one job role to another. Write a SQL query to calculate the average salary for each job role from the employees table.
Example Input:
| employee_id | first_name | last_name | job_role | salary |
|---|---|---|---|---|
| 1001 | John | Doe | Software Engineer | 85000 |
| 1002 | Jane | Smith | Data Analyst | 75000 |
| 1003 | Richard | Roe | Software Engineer | 90000 |
| 1004 | Julia | Brown | Product Manager | 100000 |
| 1005 | Emily | Black | Data Analyst | 80000 |
Example Output:
| job_role | avg_salary |
|---|---|
| Software Engineer | 87500 |
| Data Analyst | 77500 |
| Product Manager | 100000 |
Answer:
This SQL query uses the AVG function to calculate the average salary for each job role. The GROUP BY statement is used to group the salaries by job role.
To practice a very similar question try this interactive LinkedIn Duplicate Job Listings Question which is similar for requiring count and grouping by job roles or this Amazon Average Review Ratings Question which is similar for requiring calculation of average value grouped by a certain category.
SQL Question 3: Are NULLs handled the same as zero's and blank spaces in SQL?
A value represents a missing or unknown value. It is different from a zero or a blank space, which are actual values.
It's important to handle values properly in SQL because they can cause unexpected results if not treated correctly. For example, comparisons involving values always result in . Also values are not included in calculations. For example, will ignore values in the column.
SQL Question 4: Analyzing Click-through Rates for Alight Solutions
Alight Solutions is an HR services provider that offers a platform for both employees and employers. Among its numerous features, the platform allows employers to post various job opportunities which potential candidates can click on for more information.
Your task is to determine the click-through conversion rates by calculating the percentage of users who added a job opportunity to their favourites (indicating interest) after viewing. In this scenario, a 'click-through' is recording whenever a user views a job posting, and a 'conversion' is when a user adds a job posting to their favourites.
Here is the sample data:
Example Input:
Example Input:
Answer:
We need to inner join 'views' and 'favorites' tables on users and job postings and then calculate the conversion rates.
This query will return the conversion rates for each job_id based on the viewers who later added the job to their favorites. The denominator in the calculation of conversion_rate is cast to a decimal to avoid integer division. We ensure in the join condition that the favorite_date is not earlier than the view_date.
To practice a similar problem about calculating rates, solve this SQL interview question from TikTok within DataLemur's online SQL code editor:
SQL Question 5: What is the role of the constraint in SQL?
A is like a secret code that unlocks the door to another table. It's a field in one table that points to the (the master key) in another table. This helps keep the data in your database organized and tidy, because it won't let you add new rows to the table unless they have the correct secret code (a corresponding entry in the table).
It's also like a special bond between the two tables - if you try to delete the data, the will be like "Whoa, hold on! I still need that information!" and prevent the deletion from happening.
SQL Question 6: Average Client Satisfaction Score per Service
As a database specialist at Alight Solutions, you have been assigned the task of monitoring the performance of each service on a monthly basis and identifying areas where customer satisfaction needs improvement. In particular, you're required to query the table and calculate the average for each on a monthly basis.
Example Input:
| feedback_id | client_id | submit_date | service | satisfaction_score |
|---|---|---|---|---|
| 101 | 1 | 02/15/2022 00:00:00 | Payroll | 3 |
| 102 | 2 | 02/18/2022 00:00:00 | Benefits Administration | 4 |
| 103 | 3 | 02/28/2022 00:00:00 | Payroll | 5 |
| 104 | 4 | 03/01/2022 00:00:00 | Benefits Administration | 2 |
| 105 | 5 | 03/12/2022 00:00:00 | Payroll | 4 |
Example Output:
| mth | service | avg_satisfaction_score |
|---|---|---|
| 2 | Payroll | 4.00 |
| 2 | Benefits Administration | 4.00 |
| 3 | Benefits Administration | 2.00 |
| 3 | Payroll | 4.00 |
Answer:
With this query, we are grouping the data first by the month (extracted from the submit date) and then by the service. The function is then used to calculate the average satisfaction score for each group, which gives us insight into the average client satisfaction per service on a monthly basis.
SQL Question 7: What's the difference between a one-to-one vs. a one-to-many relationship between two entities? Give examples.
In database schema design, a one-to-one relationship between two entities is where each entity is associated with only one instance of the other entity. For example, the relationship between a US citizen and their social-security number (SSN) is one-to-one, because each citizen can only have one SSN, and each SSN belongs to exactly one person.
On the other hand, a one-to-many relationship is where one entity can be associated with multiple instances of the 2nd entity. For example, each person can be associated with multiple email addresses, but each email address only relates back to one person.
SQL Question 8: Alight Solutions Employee Holiday Request Analysis
As a database admin for Alight Solutions human resource department, you want to know how many days off employees took on average each month in 2021. Your task is to write a SQL query to calculate this information using the table, which has the following structure:
Example Input:
| employee_id | start_date | end_date |
|---|---|---|
| 7542 | 2021-06-22 | 2021-06-24 |
| 4845 | 2021-05-01 | 2021-05-05 |
| 6351 | 2021-12-24 | 2021-12-28 |
| 9636 | 2021-03-01 | 2021-03-01 |
| 8426 | 2021-09-10 | 2021-09-15 |
Each row in the table represents one employee's request for time off, with the start and end dates of the period they were not working. Note that the start and end dates are inclusive.
Expected Output:
| month | average_days_off |
|---|---|
| 3 | 1 |
| 5 | 5 |
| 6 | 3 |
| 9 | 6 |
| 12 | 5 |
Answer:
This query solves the problem by first filtering the records that fall into 2021. Then it groups the records by the month of the , and for each group, it calculates the average number of days off. The is necessary in the function to make both the start and end date inclusive. The and functions are PostgreSQL-specific functions to get the month and year parts from a timestamp respectively.
How To Prepare for the Alight Solutions SQL Interview
The best way to prepare for a Alight Solutions SQL interview is to practice, practice, practice.
In addition to solving the earlier Alight Solutions SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Google, Facebook, Microsoft and Amazon.
Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there is an online SQL code editor so you can right online code up your SQL query answer and have it checked.
To prep for the Alight Solutions SQL interview it is also wise to practice SQL problems from other tech companies like:
But if your SQL query skills are weak, don't worry about going right into solving questions – improve your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers things like Self-Joins and AND/OR/NOT – both of these pop up routinely in Alight Solutions SQL interviews.
Alight Data Science Interview Tips
What Do Alight Solutions Data Science Interviews Cover?
In addition to SQL query questions, the other types of questions covered in the Alight Solutions Data Science Interview are:
- Probability & Stats Questions
- Python or R Coding Questions
- Product Analytics Questions
- Machine Learning Questions
- Behavioral & Resume-Based Questions
How To Prepare for Alight Solutions Data Science Interviews?
The best way to prepare for Alight Solutions Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG, tech startups, and Wall Street
- A Crash Course on SQL, AB Testing & ML
- Great Reviews (900+ reviews, 4.5-star rating)