11 TransDigm SQL Interview Questions (Updated 2024)

Updated on

December 7, 2023

At TransDigm Group, SQL us crucial for analyzing components sales data, and predicting future demand trends in the aerospace industry. Because of this, TransDigm almost always evaluates jobseekers on SQL coding questions in interviews for Business Analyst, Data Analyst, and Data Science jobs.

So, if you want to ace the SQL Assessment, we've curated 11 TransDigm Group SQL interview questions to practice, which are similar to commonly asked questions at TransDigm – can you solve them?

TransDigm Group

11 TransDigm Group SQL Interview Questions

SQL Question 1: Find the Power Users for TransDigm

For the company TransDigm, which sells aircraft components, a power user could be defined as a customer who consistently places large orders. You are requested to find out those power users who have placed total orders worth more than $500,000 within a single year.

For this scenario, let's assume that we have the following table schema:

Example Input:
123Airways Limited
265Aviation Corp.
362Rolls Plane
Example Input:


This query first joins the customer and orders table on the customer_id, thereby relating customer's data with their respective order data. The WHERE clause filters out the orders that are not in 2021. Then, it aggregates the amount of orders for each customer using GROUP BY clause, and the HAVING clause filters out customers who have placed orders worth less than $500,000, thus giving us the list of power users.

Note: The dollar figures and time frame in the problem are both arbitrary and can be adjusted for different definitions of a "power user".

To solve a super-customer analysis question on DataLemur's free online SQL coding environment, try this Microsoft Azure Cloud SQL Interview Question:

Microsoft SQL Interview Question: Super Cloud Customer

SQL Question 2: Cumulative Monthly Sales Analysis

As TransDigm provides aircraft components, we will use a table which represents the sale records of aircraft parts. The question is to find out the monthly cumulative sale quantity of each product up to a certain date.

Here are some sample tables:

Example Input:
Example Output:


Below is the SQL query to answer the question:

This SQL query uses the window function SUM to calculate the cumulative quantity of each product sold up to a certain month. The PARTITION BY clause divides the sales data into partitions based on . The ORDER BY clause in the OVER() clause sorts these partitions by , and the function then calculates the running total quantity within each partition. The ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW means that all rows from the start of the partition up to (and including) the current row are included in the calculation. The final result is sorted by and .

For more window function practice, try this Uber SQL Interview Question within DataLemur's online SQL code editor:

Uber Window Function SQL Interview Question

SQL QUESTION 3: What are SQL constraints, and can you give some examples?

In a database, constraints are rules that the DBMS (database management system) follows when performing operations such as inserting, updating, or deleting data.

For example, consider a table of employee records at TransDigm. Some constraints that you might want to implement include:

  • NOT NULL: This constraint ensures that certain columns, such as the employee's first and last name, cannot be NULL.
  • UNIQUE: This constraint ensures that each employee has a unique employee ID.
  • PRIMARY KEY: This constraint combines the NOT NULL and UNIQUE constraints to create a primary key for the employee table. The primary key is a column or set of columns that uniquely identifies each row in the table.
  • FOREIGN KEY: This constraint establishes a relationship between the employee table and other tables in the database. For example, you could use a foreign key to link the employee ID to the department ID in a department table to track which department each employee belongs to.
  • DEFAULT: This constraint specifies a default value for a column in case no value is specified when a new row is inserted into the table.

SQL Question 4: Filtering TransDigm Customers Based on Purchase History and Location

As a data analyst at TransDigm, you are tasked with tracking customer behavior and segmenting them based on geography and purchase patterns. This information would help the marketing team to strategically position their products and optimize their advertising budget.

To better understand this, you are requested to find all customers from the West Coast of the United States (California, Oregon and Washington) who have spent more than $10,000 on TransDigm's aerospace materials in the year 2021.

Example Input:
Example Input:


This query first joins the and tables using the field.

It then filters for records where the customer's location is either California, Oregon, or Washington and the sale occurred in the year 2021.

The clause groups these records by customer id, customer name, and location, and the condition further filters groups where the total spent is greater than 10,000.TheresultisalistofcustomersfromtheWestCoastwhospentover10,000. The result is a list of customers from the West Coast who spent over 10,000 on aerospace materials in 2021.

SQL QUESTION 5: Could you describe the function of UNION in SQL?

The UNION operator combines the results from multiple SELECT statements into a single result set.

Here's an example of using the UNION operator to combine the results of two SELECT statements that retrieve data from tables of TransDigm's Facebook ads and their Google ads:

This statement would return a combined result set of both Facebook and Google ads that have a spend greater than $200. The result set would include the following columns: ad_id, ad_name, ad_type, impressions, clicks, and spend.

Note that the two SELECT statements within the UNION must have the same number of columns and the columns must have similar data types. In this example, both SELECT statements have the same number of columns and the data types of the columns are all compatible.

SQL Question 6: Average Price per Sold Aircraft Part

TransDigm maintains a sales database with each individual transaction and they want to check the average price of each aircraft part sold last year.

Given a table that has , , , and columns, write a SQL query that returns the average price for each part number sold in the year 2021.

Example Input:
Example Output:


This SQL script starts by selecting the part_number and the average sale_price from the sales table. It then filters the data to only include sales from the year 2021. The GROUP BY clause is used to create separate averages for each part_number. The result is a list of part_numbers along with their average sale_price for the year 2021.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for handling sales data and averages or this Wayfair Y-on-Y Growth Rate Question which is similar for working with sales data over a period of time.

SQL QUESTION 7: What does the constraint do?

A UNIQUE constraint ensures that all values in a column are different. It is often used in conjunction with other constraints, such as NOT NULL, to ensure that the data meets certain conditions.

For example, if you had TransDigm sales leads data stored in a database, here's some constraints you'd use:

In this example, the UNIQUE constraint is applied to the "email" and "phone" fields to ensure that each TransDigm lead has a unique email address and phone number. This helps to ensure the integrity of the data in the database and prevents errors that could occur if two leads had the same email address or phone number.

SQL Question 8: Average Order Price per Month for Each Product

As a Data Analyst at TransDigm one of your tasks is to track the average price of each product's order for each month using the Sales Orders data.

Example Input:

You are to write an SQL query that returns the month of order (in the YYYY-MM format), product_id, and the average price for each product id per month.

Example Output:


This SQL query first transforms the to a string format that includes only year and month (YYYY-MM). It groups the data first by this newly created and then by . The aggregate function computes the average order price per month for each product.

SQL Question 9: Detailed Sales Report Analysis

As a data analyst at TransDigm, you are working on a sales analysis project. You are given two tables:

  1. - Which contains information about customers such as customer_id, first_name, last_name, and country.
  2. - Which logs every sale, each with sale_id, customer_id, product_id, quantity, sale_date, and total_price.

Most recent sales should be considered for this analysis. If a product has never been sold, it should not appear in the output. Write a SQL query that will give you a detailed sales report, showing how much product each customer has bought, sorted by total quantity in descending order.

Example Input:
Example Input:


Explanation of the answer:

This SQL query first performs a JOIN operation to combine the table with the table based on the matching in both tables. It then groups the result by customer names (both and ) and .

Finally, it calculates the total quantity of products bought by each customer using the function. The records are ordered in descending order of the total quantity. This gives a report showing how much of each product each customer has purchased.

Because joins come up frequently during SQL interviews, try this interactive Snapchat JOIN SQL interview question:

Snapchat Join SQL question

SQL QUESTION 10: What's denormalization, and when does it make sense to do it?

Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).

For example, in a database that stores TransDigm sales analytics data, you might have separate tables for "customers," "orders," and "products," with foreign key constraints linking the tables together. This helps to ensure the integrity of the data and reduces redundancy, but it can also make queries that involve multiple tables more complex and slower to execute.

By de-normalizing the database, you can combine some of the data from separate tables into a single table, which can reduce the number of joins that are required to retrieve the data you need. This can speed up queries and improve the performance of your database.

However, it's important to carefully consider the trade-offs of de-normalization before making any changes to your database. De-normalization can make it more difficult to maintain the integrity and reliability of your data, and can also increase the risk of data redundancy. It's generally best to use de-normalization as a performance optimization technique only when necessary, and to carefully evaluate the benefits and drawbacks in the context of your specific database and workload.

SQL Question 11: Calculate Monthly Product Revenue with Mathematical Functions

Each TransDigm product has its own price and the quantity sold in each transaction may be different.

Given table , can you write a SQL query to calculate the total revenue (price multiplied by quantity sold) for each product for each month? The price needs to be rounded to two decimal places.

Please use function to round the total revenue to 2 decimal places, and use date functions to group revenue into months.

Example Input:
1257A106/15/2022 00:00:0010150.55
2625A206/20/2022 00:00:005210.35
4312A106/30/2022 00:00:007150.55
5887A306/30/2022 00:00:00390.20
6654A207/01/2022 00:00:004210.35
Example Output:


This answer first calculates the revenue from each sale (price per unit multiplied by quantity sold), then groups by the month of sale date and product_id to calculate the total revenue per product per month. The rounding function ensures that the final total revenue has a precision of two decimal places. The final results are then ordered by month and product for ease of understanding.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating revenue from product sales or this CVS Health Pharmacy Analytics (Part 1) Question which is similar for calculating profits.

TransDigm SQL Interview Tips

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the TransDigm SQL interview is to solve as many practice SQL interview questions as you can!

Besides solving the above TransDigm SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like FAANG and tech startups. DataLemur Questions

Each SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive coding environment so you can right online code up your SQL query answer and have it checked.

To prep for the TransDigm SQL interview you can also be helpful to solve SQL questions from other defense & aerospace contractors like:

But if your SQL query skills are weak, don't worry about jumping right into solving questions – improve your SQL foundations with this DataLemur SQL Tutorial.

SQL tutorial for Data Scientists & Analysts

This tutorial covers things like advantages of CTEs vs. subqueries and Self-Joins – both of which come up often during SQL job interviews at TransDigm.

TransDigm Group Data Science Interview Tips

What Do TransDigm Data Science Interviews Cover?

For the TransDigm Data Science Interview, beyond writing SQL queries, the other types of questions to prepare for are:

  • Statistics and Probability Questions
  • Coding Questions in Python or R
  • Product Analytics Questions
  • Machine Learning Questions
  • Behavioral Interview Questions

How To Prepare for TransDigm Data Science Interviews?

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