11 Boeing SQL Interview Questions (Updated 2024)

Updated on

December 6, 2023

SQL is used all the damn time at Boeing for analyzing airplane engine sensor data for efficiency improvements, and for managing the database systems which store info on manufacturing and supply chain operations. That's why Boeing frequently asks SQL query questions during interviews for Data Analytics, Data Science, and Data Engineering jobs.

In case you're stressed about an upcoming SQL Interview, we've collected 10 Boeing SQL interview questions to practice, which are similar to recently asked questions at Boeing – can you solve them?

Boeing SQL Questions

10 Boeing SQL Interview Questions

SQL Question 1: Defining Power Customers for Boeing

Boeing would like to consider their power customers as those companies or airlines who purchase more than average number of aircraft within a year. The question is to identify these companies from Boeing's sales database. You are given a table , which records all sales transactions.

sales Example Input:


Write a SQL query to identify these power customers on a yearly basis, given a cut-off sale count (for example, 10 purchases per year).


Given the question, here is how you could write the SQL block containing the answer:

This SQL query will group all sales by customer_id and year, and then filter out the groups where the total number of sales (or purchases) is greater than 10. These groups are our power customers for each year.

Note: This query assumes that the is stored in a correct date or datetime format in the Boeing's database so that the YEAR() function can be used. If not, you will need to convert it into correct format first before using YEAR() function.

To solve a related super-user data analysis question on DataLemur's free online SQL code editor, try this Microsoft Teams Power User SQL Interview Question:

Microsoft SQL Interview Question: Teams Super User

SQL Question 2: Aircraft Utilization Rate

At Boeing, one important metric is the utilization rate of each aircraft model, which is the ratio of total flight hours to total hours available for each aircraft. Let's assume you have access to the and tables in the Boeing database.

The question is: Write a SQL query to calculate the utilization rate of each aircraft for every day. The utilization rate is defined as the total flight hours divided by the total hours available for each aircraft.

The table tracks each flight's departure time, arrival time, and aircraft ID associated with that flight.

Example Input:
1A3202022-06-08 10:00:002022-06-08 12:00:00
2A3202022-06-09 15:00:002022-06-09 17:00:00
37772022-06-26 08:00:002022-06-26 12:00:00
47772022-07-01 20:00:002022-07-01 22:00:00
5A3802022-07-05 11:00:002022-07-05 15:00:00

The table stores the aircraft ID and the total hours that aircraft is available for a flight each day.

Example Input:

Example Output:


In this query, we use the window function to segment the data by day and aircraft ID. We calculate the total flight hours for each aircraft by using between the departure and arrival times. Then we join the table with the table to know each aircraft's daily total availability, which we use to calculate the utilization rate.

To practice a related window function SQL problem on DataLemur's free online SQL code editor, try this Amazon SQL question asked in a BI Engineer interview: Amazon SQL Interview Question

SQL QUESTION 3: In database design, what do foreign keys do?

A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables.

SQL Question 4: Filter Aircraft Data Based on Conditions

As a data analyst for Boeing, you are tasked to filter out specific records from the company's aircraft database. Your manager wants to see all aircrafts that have a range greater than 5000 miles, and produced either before the year 2000 or after the year 2010. The manager also specifically does not want to see any aircrafts that are part of the 737 series.

Your task is to write a SQL query to filter down the aircraft records based on these conditions.

Example Input:
Example Output:


The SQL query filters on the criteria given by the manager. It first filters for aircrafts with a range greater than 5000 miles. In the next criteria, it checks for aircraft manufactured before the year 2000 or after 2010. Finally, it excludes any 737 series aircraft from the results. Output consists of aircraft records that fulfill all these conditions.

SQL QUESTION 5: What's the difference between a clustered and non-clustered index?

Here is an example of a clustered index on the column of a table of Boeing customer transactions:

This creates a clustered index on the column, which will determine the physical order of the data rows in the table.

Here is an example of a non-clustered index on the column of the same table:

This will create a non-clustered index on the column, which will not affect the physical order of the data rows in the table.

In terms of query performance, a clustered index is usually faster for searches that return a large number of records, while a non-clustered index is faster for searches that return a small number of records. However, updates to a clustered index are slower, as they require the data rows to be physically rearranged, while updates to a non-clustered index are faster, as they only require the index data structure to be updated.

SQL Question 6: Average Manufacturing Costs by Aircraft Model and Year

Given an aircraft manufacturing dataset, write an SQL query to compute the average manufacturing cost per aircraft model per year. Assume there are two tables, and .

Here's the example input:

Example Input:
Example Input:

We want to find out the average manufacturing cost per aircraft model per year, which could be useful for financial and strategic planning.


This query first performs an INNER JOIN between the and tables on . It then groups by and , and for each group, it computes the average cost. The output is ordered by and to make it easier to interpret.

Example Output:

The output table shows the average manufacturing cost for each aircraft model per year. This can help Boeing understand how the manufacturing costs varied over time and among different models.

SQL QUESTION 7: What does the SQL command do?

combines the results from two or more SELECT statements, but only returns the rows that are exactly the same between the two sets.

For example, say you were doing an HR Analytics project for Boeing, and had access to Boeing's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all employees who also show up in the contractors table:

SQL Question 8: Find All Boeing Employees in Seattle

Boeing, as a leading aircraft manufacturer, has numerous employees worldwide and keeps their details in a database for administrative purposes. As an SQL expert, you have been tasked to retrieve all employee records based out of Seattle.

Use the SQL keyword to filter and choose records that have "Seattle" in their "location" field in the table.

Example Input:
101PaulBakerSeattle, WA2018-07-01
102JaneMillerChicago, IL2019-06-01
103MarkWilliamsSeattle, WA2020-05-21
104LindaBrownNew York, NY2019-03-15
105MichaelDavisSeattle, WA2021-04-18
Example Output:
101PaulBakerSeattle, WA2018-07-01
103MarkWilliamsSeattle, WA2020-05-21
105MichaelDavisSeattle, WA2021-04-18


This query will search in the table and filter out the rows where the field value starts with 'Seattle'. Thus, all Boeing employees based out of Seattle will be retrieved.

SQL Question 9: Aircraft Fuel Efficiency and Operating Costs

Given the flight data for Boeing's fleet, calculate, round off (to the nearest integer) and rank the average fuel efficiency per flight distance for each aircraft model. The fuel efficiency is measured as the ratio of the flight distance to the fuel consumption, expressed in miles per gallon (mpg). Also, using the fuel cost per gallon, calculate the total operating cost for each aircraft model.

Please refer to the sample data tables below:

Example Input:
1'737 MAX'
Example Input:
Example Input:


This SQL query first joins the aircrafts and flights tables using the aircraft_id field, calculates the average fuel efficiency (measured in miles per gallon) for each aircraft model by dividing the flight distance by the fuel consumption for each flight and then averaging the results by aircraft model. It also calculates the total operating costs by multiplying the fuel efficiency by the cost per gallon for each flight and then summing the results by aircraft model. The results are then rounded off to the nearest integer and ranked in descending order by fuel efficiency.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating total utilization or this McKinsey 3-Topping Pizzas Question which is similar for calculating cost based on component data.

In case this problem was difficult, go re-learn SQL with this DataLemur SQL tutorial which has 30+ lessons including one onn math in SQL.

SQL QUESTION 10: How do relational and non-relational databases differ?

While both types of databases are used to store data (obviously), there's some key differences in how they store and organize data.

Relational databases try to represent the world into neat little tables, with rows and columns. Non-relational (NoSQL) databases use a variety of data models to represent data, including document, key-value, columnar, and graph storage formats.

While the exact types of NoSQL databases is beyond the scope of a Data Analyst and Data Scientist SQL interivew at Boeing, it's good to know that companies generally choose to use NoSQL databases:

  • when dealing with unstructured or semi-structured data
  • when the database needs to be scaled horizontally easily
  • when the data is non-relational (like storing social network data which makes more sense in a graph format)

In case this problem was difficult, go re-learn SQL with this DataLemur SQL tutorial which has 30+ lessons including one on math in SQL.

Preparing For The Boeing SQL Interview

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.

In addition to solving the above Boeing SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Netflix, Airbnb, and Amazon.

DataLemur SQL Interview Questions

Each problem on DataLemur has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive SQL code editor so you can right online code up your SQL query answer and have it executed.

To prep for the Boeing SQL interview it is also a great idea to practice interview questions from other defense & aerospace contractors like:

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

Interactive SQL tutorial

This tutorial covers topics including window functions like RANK() and ROW_NUMBER() and using wildcards with LIKE – both of which come up often during Boeing SQL assesments.

Boeing Data Science Interview Tips

What Do Boeing Data Science Interviews Cover?

For the Boeing Data Science Interview, besides SQL questions, the other types of questions to prepare for are:

  • Probability & Statistics Questions
  • Python or R Programming Questions
  • Product Analytics Questions
  • Machine Learning Questions
  • Behavioral Interview Questions

How To Prepare for Boeing Data Science Interviews?

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

  • 201 Interview Questions from companies like Microsoft, Google & Amazon
  • A Crash Course covering SQL, Product-Sense & ML
  • Great Reviews (900+ 5-star reviews on Amazon)

Ace the Data Science Interview by Nick Singh Kevin Huo