9 Apollo Global Management SQL Interview Questions (Updated 2024)

Updated on

June 30, 2024

Data Analytics, Data Science, and Data Engineering employees at Apollo Global Management write SQL for analyzing large financial datasets and generating insightful reports. For this reason Apollo Global Management typically asks folks interviewing for data jobs SQL coding interview questions.

As such, to help you practice for the Apollo Global Management SQL interview, we'll cover 9 Apollo Global Management SQL interview questions in this article.

Apollo Global Management SQL Interview Questions

9 Apollo Global Management SQL Interview Questions

SQL Question 1: Identify the Top Performing Assets

Given the Apollo Global Management's assets portfolio, your task is to write a SQL query that returns the top 3 performing assets (in terms of income generated each month) in each financial sector over the past 12 months. The sectors are categorized as Energy, Real Estate, Private Equity, and Credit.

Example Input:
A10002AssetName2Real Estate
A10003AssetName3Private Equity
Example Input:


This query first calculates the total income for each asset per month over the last year with common table expression (CTE), . Then, it ranks the assets within each financial sector per month in another CTE, , using the window function. In the main SELECT block, it narrows down the results to the top 3 assets per sector per month.

p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur

DataLemur Window Function SQL Questions

SQL Question 2: Top Three Salaries

Suppose you had a table of Apollo Global Management employee salary data. Write a SQL query to find the top 3 highest paid employees within each department.

Apollo Global Management Example Input:

1Emma Thompson38001
2Daniel Rodriguez22301
3Olivia Smith20001
4Noah Johnson68002
5Sophia Martinez17501
8William Davis68002
10James Anderson40001

Example Input:

1Data Analytics
2Data Science

Example Output:

Data AnalyticsJames Anderson4000
Data AnalyticsEmma Thompson3800
Data AnalyticsDaniel Rodriguez2230
Data ScienceNoah Johnson6800
Data ScienceWilliam Davis6800

Try this problem directly within the browser on DataLemur:

Top 3 Department Salaries


We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.

If the solution above is tough, you can find a step-by-step solution with hints here: Top 3 Department Salaries.

SQL Question 3: What is the function of a primary key in a database?

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 Apollo Global Management 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.

Apollo Global Management SQL Interview Questions

SQL Question 4: Portfolio Investment Returns Analysis

Apollo Global Management is an investment firm that manages various portfolios. One such aspect is the amount of money invested in different companies to make a profit. You are the data scientist at Apollo Global Management and are asked to analyze the return on investments from the various companies.

You have the following tables:

Example Input:
1Apple Inc.
2Microsoft Corp.
Example Input:
Example Input:

The task is to calculate the total amount invested, total returns and the rate of return (total returns/total investments) for each company for the year 2022. Your output should be the company name, total invested amount, total returned amount, and the rate of return.


The above query first joins three tables based on their relationships. It then filters the returns for the year 2022. Next, it aggregates the investment and return amounts, and calculates the return rate by dividing the total returned amount by the total invested amount. Finally, it groups the results by the company name.

Check out the Apollo Global Career page and see what type of role might be best suited for you!

SQL Question 5: What are SQL constraints, and can you give some examples?

Constraints are used to specify the rules concerning data in the table. It can be applied for single or multiple fields in an SQL table during the creation of the table or after creating using the ALTER TABLE command. The constraints are:

Say you were storing sales analytyics data from Apollo Global Management's CRM inside a database. Here's some example constraints you could use:

  • PRIMARY KEY constraint: You might use a PRIMARY KEY constraint to ensure that each record in the database has a unique identifier. For example, you could use the "opportunity_id" field as the primary key in the "opportunities" table.

  • FOREIGN KEY constraint: You might use a FOREIGN KEY constraint to link the data in one table to the data in another table. For example, you could use a foreign key field in the "opportunities" table to reference the "account_id" field in the "accounts" table.

  • NOT NULL constraint: You might use a NOT NULL constraint to ensure that a field cannot contain a NULL value. For example, you could use a NOT NULL constraint on the "opportunity_name" field in the "opportunities" table to ensure that each opportunity has a name.

  • UNIQUE constraint: You might use a UNIQUE constraint to ensure that the data in a field is unique across the entire table. For example, you could use a UNIQUE constraint on the "email" field in the "contacts" table to ensure that each contact has a unique email address.

  • CHECK constraint: You might use a CHECK constraint to ensure that the data in a field meets certain conditions. For example, you could use a CHECK constraint to ensure that the "deal_probability" field in the "opportunities" table is a value between 0 and 100.

  • DEFAULT constraint: You might use a DEFAULT constraint to specify a default value for a field. For example, you could use a DEFAULT constraint on the "stage" field in the "opportunities" table to set the default value to "prospecting"

SQL Question 6: Filter Clients Based on Investment Types and Sizes

Apollo Global Management wants to segment their clients based on the size of their investments and the types of asset they invest in. They want to filter out clients who have investments larger than $1million and are investing in either 'Real Estate' or 'Private Equity'.

Create a SQL command that will return the , , , and from the table for clients who meet the above criteria.

Example Input:
1JohnDoe2000000Real Estate
2JaneDoe800000Private Equity
3AliceSmith1500000Private Equity
4BobBrown500000Bond Market
5CharlieClark1200000Bond Market


The output will show the , , , and of clients who have investments larger than $1million and are investing in either 'Real Estate' or 'Private Equity'. This will enable Apollo Global Management to do a focused marketing and service approach for this high-value client segment.

SQL Question 7: How do you identify duplicated data in a table?

One way to find duplicatesis to use a clause and then use to find groups

You could also use the operator:

SQL Question 8: Average Fund Returns for Apollo Global Management

Imagine you're a data analyst at Apollo Global Management, a private equity firm. You have been tasked with finding the average annual return of all the active funds managed by the company. We will consider a fund to be 'active' if it has had a return at any point in the last two years (including the current year).

The table contains information about each fund, including its and . Its schema is as follows:

Example Input
100Equity Portfolio I
101Credit Portfolio I
102Real Asset Portfolio I

The table contains information about the returns for each fund for each year, including the , , and . Its schema is as follows:

Example Input

The question is: what is the average annual return for each active fund?


This query first joins the and tables on their common field. Then it restricts the data to only the last two years using the WHERE clause. The AVG function is then used to calculate the average annual return for each active fund. The result is a list of each active fund's name and its average annual return over the last two years.

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating growth rates or this Amazon Average Review Ratings Question which is similar for computing averages.

SQL Question 9: Calculate the Click-Through-Rate for Digital Products

Given a table tracking user click behavior on digital ads and a table tracking the purchases made after clicking on the ads, calculate the click-through conversion rate for Apollo Global Management. The click-through conversion rate is defined as the number of purchases made after clicking an ad divided by the total number of clicks, expressed as a percentage.

Example Input:
112306/11/2022 00:00:001001
226506/10/2022 00:00:001002
336206/18/2022 00:00:001001
419207/26/2022 00:00:001002
598107/05/2022 00:00:001001
Example Input:
112306/11/2022 00:05:001001
226506/10/2022 00:03:001002
319207/26/2022 00:00:001002


This query first makes a left join of the and table on the columns and to combine the relevant data. It then calculates the click-through rate for each product by dividing the total number of purchases by the total number of clicks and multiplying it by 100 to get a percentage. Note that is used to ensure the division result is a decimal rather than an integer.

To solve a related problem on DataLemur's free interactive SQL code editor, attempt this Facebook SQL Interview question: Facebook App CTR SQL Interview question

Preparing For The Apollo Global Management SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Apollo Global Management SQL interview is to solve as many practice SQL interview questions as you can! In addition to solving the earlier Apollo Global Management SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Microsoft, Google, Amazon, and tech startups. DataLemur Questions

Each exercise has multiple hints, detailed solutions and crucially, there is an online SQL coding environment so you can easily right in the browser your SQL query answer and have it checked.

To prep for the Apollo Global Management SQL interview it is also a great idea to solve SQL questions from other investment management and private equity companies like:

But if your SQL foundations are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this DataLemur SQL Tutorial.

DataLemur SQL Tutorial for Data Science

This tutorial covers SQL concepts such as manipulating date/time data and aggregate functions like SUM()/COUNT()/AVG() – both of which show up frequently in Apollo Global Management SQL interviews.

Apollo Global Management Data Science Interview Tips

What Do Apollo Global Management Data Science Interviews Cover?

Beyond writing SQL queries, the other topics covered in the Apollo Global Management Data Science Interview are:

Apollo Global Management Data Scientist

How To Prepare for Apollo Global Management Data Science Interviews?

The best way to prepare for Apollo Global Management Data Science interviews is by reading Ace the Data Science Interview. The book's got:

  • 201 Interview Questions from Google, Microsoft & tech startups
  • A Crash Course on Python, SQL & ML
  • Great Reviews (1000+ 5-star reviews on Amazon)

Ace the Data Science Interview by Nick Singh Kevin Huo