10 Ameriprise Financial SQL Interview Questions (Updated 2024)

Updated on

June 30, 2024

Data Analysts and Data Engineers at Ameriprise Financial use SQL for extracting structured data for financial modeling and performing data manipulation tasks. That's why Ameriprise Financial LOVES to ask folks interviewing at the company SQL coding interview questions.

To help you prepare for the Ameriprise Financial SQL interview, here's 10 Ameriprise Financial SQL interview questions in this article.

Ameriprise Financial SQL Interview Questions

10 Ameriprise Financial SQL Interview Questions

SQL Question 1: Analyze Revenue and Transaction over Time

As a data analyst in Ameriprise Financial, you have been tasked with analyzing transactions across each month and finding the average transaction value and total number of transactions per month.

Given the following tables:

Example Input:
10132501/15/2022 00:00:003000
10249201/28/2022 00:00:004500
10332502/10/2022 00:00:002000
10449203/18/2022 00:00:001500
10532504/19/2022 00:00:003500

You must write a SQL PostgreSQL query that calculates the average and total number of transactions each month, with the output sorted by month. Indicate the month as Month-Year for easy readability.

Expected Output:


Here is a PostgreSQL query to solve the task:

This query first converts the transaction_date to month-year format using the TO_CHAR function. Then it groups the transactions by month-year and calculates the average amount (avg_amount) and count of transactions (num_transactions) for each month year. The result is then ordered by month_year.

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

SQL Interview Questions on DataLemur

SQL Question 2: Highly-Paid Employees

Given a table of Ameriprise Financial employee salary data, write a SQL query to find employees who make more than their direct manager.

Ameriprise Financial Example Input:

1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

Example Output:

3Olivia Smith

This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.

Check your SQL query for this question interactively on DataLemur:

Employees Earning More Than Their Manager


First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

If the code above is hard to understand, you can find a step-by-step solution here: Employee Salaries Higher Than Their Manager.

Check out this Ameriprise Technical Lead job listing on the Application Development team and see how your SQL experience lines up against the job description.

SQL Question 3: Give a few ways in SQL that you can identify duplicate records in a table?

"One creative way is to use the window function ROW_NUMBER() and partition by whichver columns you are loooking for duplicates in. If any row has a row_number() more than 1, then it's a duplicate!

You could also use COUNT(DISTINCT col1) vs. COUNT(*) and see if they return different numbers, indicating the prescence of duplicates!

Ameriprise Financial SQL Interview Questions

SQL Question 4: Client Investment Portfolio Analysis

Ameriprise Financial provides various financial planning and services. It's essential for them to analyze the investment portfolios of their clients to provide insightful recommendations. The company is interested in finding the number of clients who have investments in both stocks and bonds. They would like a PostgreSQL query that counts number of customers with an investment in both the investment types to make this assessment. They also want the count of investment types for these clients.

The relevant tables provided are , , and . The table has details about the clients. The table covers the different investment types like Stocks or Bonds. The table records each investment made by a client.

Example Input:
101John Doe
102Jane Smith
103David Johnson
104Laura Davis
105James Clark
Example Input:
Example Input:


This PostgreSQL query first identifies the clients who have investments in both Stocks and Bonds using the subquery. The outer query then gets the count of these clients and their respective investment types from the table. The results show the number of clients who have investments in Stocks and Bonds and the count of these investment types.

SQL Question 5: What's a database view, and what's their purpose?

Views are a lot like virtual tables, where you can take a base table and customize it (such as by hiding some data from non-admin users, or removing some random columns/rows based on business requirements).

Here's the PostgreSQL syntax for creating a view based on data in the table:

SQL Question 6: Filter Customers Based on Investment Type and Advisor

For a Ameriprise Financial, the management wants to analyze its customers' preference in investment. The management is particularly interested in customers who:

  1. Have assets greater than $500,000.
  2. Invest in either Stocks or Mutual Funds.
  3. Either have an advisor from New York or don't have any advisor.

You are required to write an SQL query to filter these records from the table.

The data is as follows:

Example Input:
2341John Doe$750,000StocksNew York
6458Jane Roe$600,000BondsBoston
7523Jim Smith$550,000Mutual FundsNew York
6987Jill Brown$450,000Mutual FundsNew York
2649Bob Jones$900,000StocksChicago


This query will return all the records that fulfill all the defined conditions. The clause is used to filter the records based on the given criteria. The logical operator is used to ensure that all conditions are met by the records, while is used to specify multiple possible values for the same column. If a customer has an assets value greater than $500,000, has their investment_type as either Stocks or Mutual Funds, and their advisor_city is either New York or they do not have an advisor, their record will be returned by this query.

SQL Question 7: What is the purpose 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 Ameriprise Financial 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.

SQL Question 8: Average Transaction Amount for Ameriprise Financial

In Ameriprise Financial, a leading financial planning and services company, data analysis plays a crucial role in gaining insights on the transaction behavior of their clients. Given a table named "transactions", each row contains information about the client's transaction including the client ID, transaction date, and transaction amount. The question is: Can you write a SQL query to find the average transaction amount for each client?

Example Input:


This SQL query groups the transaction data by client_id (which is the unique identifier for each client), and then calculates the average transaction amount for each group.

Example Output:


This result shows the average transaction amount for each client, providing meaningful insights into the transaction behavior of Ameriprise Financial's clients. This can be useful for the company in tailoring its financial services and advice for each client based on their transaction behavior.

To practice a very similar question try this interactive Uber User's Third Transaction Question which is similar for working with transaction data or this Stripe Repeated Payments Question which is similar for identifying specific transaction patterns.

SQL Question 9: Calculating Click-Through-Rate for Email Campaigns

Ameriprise Financial, a top-tier wealth management firm, regularly sends out email campaigns promoting its various financial products. Let's say that the marketing team wants to know the click-through rate (CTR) of their email campaigns. The click-through rate is the number of users who clicked on the link in the email divided by the number of emails delivered. This data could help the marketing team evaluate the efficacy of the email's content, subject line, and timing.

Given the and tables, write a query that calculates the CTR for each campaign. Assume that the table records a user's activity whenever they click through an email.

Example Input:
1011700006/08/2022 00:00:00
5478900006/10/2022 00:00:00
78901050006/18/2022 00:00:00
Example Input:
567112306/08/2022 00:00:001011
982326506/10/2022 00:00:005478
341236206/10/2022 00:00:005478
115219206/18/2022 00:00:007890
451798106/18/2022 00:00:007890


This PostgreSQL query left joins the table to the table on . It then calculates the CTR by dividing the number of click throughs (retrieved by counting the in the table) by the and multiplying by 100 to get a percentage. The function is used to ensure that the division does not perform integer division. Finally, it groups the results by and to get the CTR for each campaign. This gives a valuable insight into how each campaign is performing in terms of promoting user interaction.

To practice a similar problem about calculating rates, try this SQL interview question from TikTok on DataLemur's online SQL coding environment: Signup Activation Rate SQL Question

SQL Question 10: What is normalization?

To normalize a database, tables are divided into smaller, more specialized ones and relationships between them are defined via primary and foreign keys. This minimizes redundancy, making the database more flexible, scalable, and easier to maintain. Normalization also helps to ensure the accuracy of the data by reducing the likelihood of inconsistencies and errors.

Ameriprise Financial 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. Besides solving the earlier Ameriprise Financial 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. DataLemur Questions

Each interview 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 interactive coding environment so you can instantly run your SQL query answer and have it checked.

To prep for the Ameriprise Financial SQL interview it is also a great idea to solve SQL problems from other banking & finanacial services companies like:

However, if your SQL foundations are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this free SQL tutorial.

SQL interview tutorial

This tutorial covers SQL topics like filtering data with WHERE and LEAD window function – both of which show up often in Ameriprise Financial SQL assessments.

Ameriprise Financial Data Science Interview Tips

What Do Ameriprise Financial Data Science Interviews Cover?

Besides SQL interview questions, the other question categories to practice for the Ameriprise Financial Data Science Interview are:

  • Probability & Stats Questions
  • Coding Questions in Python or R
  • Product Data Science Interview Questions
  • Machine Learning and Predictive Modeling Questions
  • Resume-Based Behavioral Questions

Ameriprise Financial Data Scientist

How To Prepare for Ameriprise Financial Data Science Interviews?

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