11 Fidelity SQL Interview Questions (Updated 2024)

Data Science, Data Engineering and Data Analytics employees at Fidelity use SQL for extracting and analyzing financial data, and for building databases to improve data-driven investment decisions. For this reason Fidelity LOVES to ask folks interviewing at the company SQL interview questions.

So, to help you prep for the Fidelity SQL interview, we'll cover 11 Fidelity Investments SQL interview questions in this blog.

11 Fidelity Investments SQL Interview Questions

SQL Question 1: Calculate the Monthly Investment Performance

As a database administrtor at Fidelity, you have access to a large database of investor details. For each investor, you have details of their monthly investments and the current value of those investments. The Fidelity team would like to understand the performance of these investments on a monthly basis.

The 'Investments' table has the following fields:

• investor_id: An identifier for the investor
• investment_month: The month of the investment
• investment_val: The amount of investment
• current_value: The current value of the investment

Write a SQL query that calculates the monthly performance of each investor, defined as the ratio of current investment value to initial investment value for each month.

Example Input:

Expected Output:

Answer:

In this query, the main operation is to divide the current_value by investment_val for each row to get the investment_performance. We do this for each row (ie., each investment monthly record of an investor). The results are then ordered by investor_id and investment_month to group the same investor's records together and show it chronologically.

To solve a related window function SQL problem on DataLemur's free interactive SQL code editor, solve this Amazon SQL question asked in a BI Engineer interview:

SQL Question 2: Top Department Salaries

Assume you had a table of Fidelity employee salary data. Write a SQL query to find the top three highest paid employees in each department.

Fidelity Example Input:

Example Input:

Example Output:

Test your SQL query for this interview question and run your code right in DataLemur's online SQL environment:

Answer:

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.

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SQL Question 3: What does do, and when would you use this SQL command?

When using , only rows that are identical in both sets will be returned.

For a concrete example, say you were a Data Analyst supporting the Sales Analytics team at Fidelity, and data on potential sales leads lived in both Salesforce and Hubspot CRMs. To write a query to analyze leads created before 2023 started, that show up in BOTH CRMs, you would use the command:

SQL Question 4: Filter Fidelity Customers Based on Investment Details

Fidelity, a multinational financial services corporation, wishes to filter their customer database to focus on customers with certain investment behaviors. Specifically, they are looking for customers who have more than one investment account, have invested more than $10,000 in total, and have a transaction history dating back to at least one year ago. Determine these customers and their respective details from Fidelity's database.

Example Input:

Example Input:

Answer:

This query will return the ID, name, and account open date for customers who have at least one year of transaction history, have invested more than $10,000 in total, and have more than one investment account. It first checks for customers who have at least one year of transaction history. Then, it checks if the customer has more than one investment account and has invested more than$10,000 in total.

SQL Question 5: What's the purpose of the constraint?

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 Transaction Amount

As a data analyst at Fidelity, you are asked to analyze the data of client transactions. Could you write a SQL query that determines the average transaction amount of each client over the past year?

Example Input:

Example Output:

Answer:

This query first filters out the transactions that were within the past year. It then calculates the average transaction amount for each client by grouping the transactions by client_id and then applying the AVG() function to the amount.

To practice a very similar question try this interactive Stripe Repeated Payments Question which is similar for dealing with transaction data or this Uber User's Third Transaction Question which is similar for focusing on user transactions.

SQL Question 7: How are and similar, and how are they different?

Both window functions are used to find rows at a given offset from the current row. However, will give you the rows AFTER the current row you. On the other hand, will give you the rows BEFORE the current row.

SQL Question 8: Calculate the average balance by account type

Fidelity offers several types of accounts such as checking, savings, retirement, etc. Your task is to find the average balance in each type of account for the company Fidelity.

Assume there's a table called which tracks balance of each user.

Example Input:

Answer:

This query is using the clause to group rows that have the same values in the column. Then, it uses the function to calculate the average balance for each group.

Example Output:

In the result, you can see the average balance for each type of accounts. It's determined by the group formed by the account_type and the average function.

SQL Question 9: Finding Customer Email Addresses With Special Patterns

As a part of Fidelity's marketing initiative, you have been tasked to identify all the customer email addresses that end with '@gmail.com'. Therefore, you need to write an SQL query to search for these particular email addresses from Fidelity's customer database.

The customer database is structured as follows:

Example Input:

Answer:

You can achieve this by using the keyword in your clause. Here is an appropriate SQL query using PostgreSQL syntax:

This query selects the , , , and from the table where ends with '@gmail.com'. The '%' character is a wildcard that matches any sequence of characters.

After executing the above query, it will filter out the table and will display only those customers whose ends with '@gmail.com'.

Example Output:

SQL Question 10: Could you clarify the difference between a left and a right join?

Both types of joins in SQL help you retrieve data from multiple tables and merge the results into a single table.

To demonstrate the difference between a left join versus a right join, imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.

A retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.

A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.

SQL Question 11: Analyzing Customer and Account Data

Suppose you work for Fidelity Investments as a data analyst. In your job, you often use SQL to analyze customer and account data. One day, your supervisor asks you to analyze the customer database and join this table with the account table to get an understanding of different geographical areas' investment patterns.

Write a SQL query to find the total amount invested by customers in different states.

Here are the and tables for your SQL query:

Example Input:

Example Input:

Answer:

This query joins the customer and account tables on . It then groups the resulting table by state and calculates the total balance (or total investment) for each state. The result is an overview of the total investment amounts by state. It could be particularly helpful for understanding the investment patterns in different geographical regions.

Since join questions come up routinely during SQL interviews, try this interactive Snapchat SQL Interview question using JOINS:

Fidelity 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. Beyond just solving the above Fidelity SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups.

Each exercise has multiple hints, detailed solutions and best of all, there is an interactive coding environment so you can right in the browser run your SQL query answer and have it executed.

To prep for the Fidelity SQL interview you can also be useful to solve SQL problems from other investment management and private equity companies like:

• Vanguard SQL questions

• Charles Schwab SQL questions

• Interactive Brokers SQL questions

• Robinhood SQL questions

But if your SQL coding skills are weak, don't worry about going right into solving questions – go learn SQL with this free SQL tutorial.

This tutorial covers SQL topics like creating pairs via SELF-JOINs and AND/OR/NOT – both of these show up often in Fidelity SQL interviews.

Fidelity Investments Data Science Interview Tips

What Do Fidelity Data Science Interviews Cover?

In addition to SQL interview questions, the other question categories covered in the Fidelity Data Science Interview are:

• Statistics & AB Testing Questions
• Coding Questions in Python or R
• Analytics and Product-Metrics Questions
• ML Interview Questions
• Behavioral & Resume-Based Questions

How To Prepare for Fidelity Data Science Interviews?

To prepare for Fidelity Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from Facebook, Google, & Amazon
• a crash course covering SQL, Product-Sense & ML
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