Business Intelligence Engineer Amazon Interview


Never miss a post!

Sign up for our newsletter and get FREE Development Trends delivered directly to your inbox.

You can unsubscribe any time. Terms & Conditions.

So, are you preparing for business intelligence engineer amazon interviews and looking to understand the complete interview process and common interview questions asked at Amazon? Well, you have landed at the right place. In this blog, I will focus on the interview process at Amazon for BI engineers and what they should know before going for the interview. This is both for anyone who is preparing for their upcoming interview at amazon. So, let us get started!

BI Engineers at Amazon

At Amazon, the business intelligence engineers work with clients, product managers, data scientists and database, developers to actually translate data into an efficient collection process while also being able to drive business decisions with dashboarding tools and ETL jobs frequently. The amazon business intelligence engineers are embedded within the organization across 100 different teams and so what you will typically see is a data scientist, a couple of business intelligence engineers, a couple of data engineers, product managers, software engineers within every single product team.

Amazon BI Engineer Interview Process

So what is the interview like for the amazon business intelligence engineer, BI engineer for short. The BI engineer interview process is like every other interview process at Amazon. There is a hiring manager interview, a technical screening in SQL, and then an on-site interview where you meet with a variety of different people on the team as well as an executive that quizzes you on the amazon leadership principles.

Initial Screening Round

First off is initial screening, so this is where they just come in, and they ask you about standard behavioral questions. So, for example, they would ask something like, give me an example of a time where you had used data to make a decision about something or tell me about the most complex problem that you ever worked with. Here, they are just really trying to understand if your background fits the job description or not. They are also checking if you are a good candidate for the role, who can you communicate well to the hiring manager or the recruiter, and can you also display a general business impact that you have done in the past.

Technical Screening Round

The next part of the interview is the technical screening. In this part of the interview, they go over a cascading level of increasingly difficult SQL questions until you get to around five or six SQL questions total. So, for example, they will give you like an orders table, and a customer table and they will ask you something easy like give me the total amount of orders of all time. And then, as they increase in difficulty, it will be something like give me the top five orders created last week, give me the distribution of orders over the previous year, etc., so remember to practice SQL well.

On-Site Interview or Virtual Interview Round

The last part of the interview is the on-site interview or virtual interview due to covid. This might happen all for one day or else over a progression of a week, where you do one interview per week essentially. The process they follow is they have you interviewed with the data scientists, the hiring manager, an executive, and then also a couple of business intelligence engineers.

The questions in this interview round span across the whole breadth of data science, specifically around amazon’s problems. So, a lot of them can be behavioral questions that are going to be leadership interview questions. They will basically ask you about a time or a situation where you had to overcome a problem. Essentially, they ask you this every single time because you have to apply one of amazon’s leadership principles to that question for the first part of the interview. The second part of the interview is going to be more technical in nature, and so they can ask you anything about statistics and SQL interview questions, probability, also case questions that go around database design and ETL.

Tips for Business Intelligence Amazon Interviews

A couple of good tips for the Amazon business intelligence interview is to use the STAR framework. The star framework stands for Situation, Task, action, and then Results. So essentially, what you do is you basically create a situation, and that is usually the problem at hand, and then you have a task that you actually have to address, and then basically the action part is what actions do you do to address those problems and then the results is what are the results of those actions that you took. So this framework is really good for handling any kind of behavioral Interview and also case interview that amazon throws at you.

Common Business Intelligence Amazon Interview Questions

Here are some common interview questions that have been reported were asked in a business intelligence amazon interview.

Q1. The probability of a product coming from location A is 0.8 and from location B is 0.6. What is the probability that customers will receive the product from location A or location B?




Assuming the events are independent:

P(A OR B) = 1 – P(not A AND not B) = 1-(0.2*0.4) = 1-0.08 = 0.92

The other ways:

P(A or B) = P(A) + P(B) – P(A AND B) = 0.8 + 0.6 – (0.8*0.6) = 1.4 – 0.48 = 0.92




P(A or B) = P(A) + P(B )*P(not A) = 0.8 + (0.6*0.2) = 0.8 + 0.12 = 0.92


P(A OR B) = P(B) + P(A)*P(not B) = 0.6 + (0.8*0.4) = 0.6 + 0.32= 0.92.


Q2. What is the difference between OLAP and OLTP?

A2. OLAP and OLTP are both online processing systems. OLAP is an analytical processing system, whereas OLTP is a transactional processing system. OLAP is an online system that reports to multidimensional analytical queries like financial reporting, forecasting, etc. OLTP is a system that manages transaction-oriented applications on the internet, for example, ATM.

Q3. How would you set up an online A/B testing scenario, and how would you determine whether or not to roll out a new program given the results of the experiment?

A3. Below are the steps for performing an A/B test and evaluating the result:

Before A/B Test

  • Pick one variable to test
  • Identify your goal
  • Create a ‘control’ and a ‘challenger.’
  • Split your sample groups equally and randomly.
  • Determine your sample size (if applicable).
  • Decide how significant your results need to be.
  • Make sure you’re only running one test at a time on any campaign.

During A/B Test

  • Use an A/B testing tool.
  • Test both variations simultaneously.
  • Give the A/B test enough time to produce useful data.
  • Ask for feedback from real users.

After A/B Test

  • Focus on your goal metric.
  • Measure the significance of your results using our A/B testing calculator.
  • Take action based on your results.
  • Plan your next A/B test.

Q4. What are the different ways of query optimization and performance tuning?

A4. Below are few common ways of query optimization and performance tuning:

  • Use proper indexing to ensure quicker access to the database
  • Use SELECT <columns> instead of SELECT *
  • Avoid running queries in a loop
  • Create joins with INNER JOIN (not WHERE)
  • Use wildcards at the end of a phrase only
  • Drop index before loading bulk data
  • Use WHERE instead of HAVING to define filters
  • Run your query during off-peak hours

Q5. You have a website, and you need to report the traffic insights on this website to the Product Manager. Write an SQL query to find the top 10 persons who have visited the website in the last month.

A5. select customer_id,count(*) from table where eff_dt between current_date and current_date-30 group by customer_id order by count(*) desc fetch first 10 rows only;

Q6. What are the assumptions in a random forest model?

A6. No formal distributional assumptions, random forests are non-parametric and can thus handle skewed and multi-modal data as well as categorical data that are ordinal or non-ordinal.

Q7. What is the use of statistical analysis?

A7. Statistical analysis applies specific statistical methods to a sample of data to have an understanding of the total population. It allows for conclusions to be drawn about specific markets, cohorts, and a general grouping to potentially predict the behaviour and characteristics of others.

Final Thoughts

So that was all about the business intelligence amazon interview I wanted to discuss. I how now have a fair understanding of the interviews taken by Amazon and their processes. Start preparing based on the insights I have mentioned in this article. I hope these details will help you in getting a kickstart to your future BI amazon interviews. So, prepare well and all the best!


Our website uses cookies that help it to function, allow us to analyze how you interact with it, and help us to improve its performance. By using our website you agree by our Terms and Conditions and Privacy Policy.