20 Questions from the Amazon Business Intelligence Engineer (BIE) Interview

Updated on

January 29, 2024

Don't underestimate the Amazon Business Intelligence Engineer (BIE) Interview – between the lengthy interview process, bar-raiser rounds, and high-stakes, this process can be trickier than you might expect.

In the article, we will learn the intricacies of the BIE role at Amazon, uncover the responsibilities that come with it, and unravel the rounds of the Amazon interview process. So let’s get started!

Amazon BIE Interbiew Guide

What does a Business Intelligence Engineer do at Amazon?

The role of a Business Intelligence Engineer (BIE) revolves around harnessing data to drive strategic decision-making. They play a crucial part in deciphering complex datasets, developing insightful analyses, and presenting actionable recommendations to key stakeholders.

Amazon relies on its BIEs to transform raw data into meaningful insights, contributing directly to the company's success by enhancing operational efficiency, optimizing processes, and providing a data-driven foundation for innovation.

Amazon Workplace

Amazon sells over 353 million products across 173 countries. With such a gigantic scale of business, they need to rely on a team of BIEs to make timely decisions across the functions to thrive in a competitive environment.

Amazon BIE Job Responsibilities

Business intelligence engineers (BIEs) build out a variety of analytics. As a BIE, you’ll define key performance indicators (KPIs), automate data pipelines, and create reports, dashboards, and visualizations. BIEs at Amazon are good at statistics, data processing, data visualization, and Extract, Transform, and Load (ETL). BIEs can translate between business needs and data so that no decision is taken without data-backed evidence.

  1. Data Analysis and Interpretation: BIEs at Amazon are responsible for analyzing large datasets, identifying trends, and extracting valuable insights to inform business decisions.
  2. Report Development and Visualization: BIEs create comprehensive reports and visually appealing dashboards, enabling teams to easily grasp and act upon critical information.
  3. Business Process Optimization: These engineers work on optimizing business processes by utilizing data analytics to identify areas for improvement and streamline operations.
  4. Forecasting and Predictive Modeling: BIEs leverage advanced statistical methods to develop forecasting models, aiding Amazon in anticipating future trends and market dynamics. BIEs design, develop and maintain data and machine learning pipelines to ensure continuous delivery of business intelligence.
  5. Collaboration with Cross-functional Teams: BIEs collaborate with diverse teams, including data scientists, engineers, and business leaders, to ensure the alignment of data strategies with overarching business objectives.

Qualifications and Skills Required to be a Business Intelligence Engineer

To thrive as an Amazon Business Intelligence Engineer, candidates should possess a blend of technical proficiency and analytical prowess. Key qualifications and skills include:

  1. Educational Background: A bachelor's or advanced degree in a relevant field such as Computer Science, Statistics, or Business Analytics.
  2. Programming Skills: Proficiency in programming languages such as SQL, Python, or R is essential for manipulating and analyzing data. Familiarity with data structures, algorithms, machine learning, and analytical techniques
  3. Data Warehousing: Familiarity with data warehousing concepts such as ETL and tools, as BIEs often work with large-scale data stored in Amazon Redshift or similar platforms.
  4. Statistical Analysis: A strong foundation in statistical methods and the ability to apply them to solve complex business problems.
  5. Data Visualization: Skills in data visualization tools like Tableau or Power BI to effectively communicate findings to diverse audiences.
  6. Business Acumen: An understanding of business operations and the ability to translate business requirements into meaningful data solutions.

How to prepare for the Business Intelligence Engineer (BIE) Interview

The interview process for Amazon BIE can be divided into three main stages:

Application and Screening

The journey begins with the application and screening stage. Amazon is keen on candidates who showcase a strong foundation in data analytics and problem-solving. Be prepared for initial questions about your background, and experiences, and a brief overview of your technical skills.

Technical Screen

The Technical Screen is designed to assess your technical proficiency. Expect questions related to SQL, data manipulation, and basic problem-solving scenarios. Demonstrate your ability to navigate through datasets, write efficient queries, and solve analytical problems. Brush up on your coding skills, and practice solving problems under time constraints.

Behavioral/On-site Interviews

In the Behavioral/On-site Interviews, Amazon evaluates your soft skills, problem-solving approach, and cultural fit. Questions may delve into your past experiences, challenges faced, and your alignment with Amazon's leadership principles. Research Amazon's 16 leadership principles and tailor your answers accordingly. For more information about how to Ace your Amazon Behavioral Interview read this guide.

Bar Raiser Round

The Bar Raiser Round is a unique and challenging aspect of Amazon's behvarioal interview process. This round involves an additional interviewer, often from a different department, ensuring the candidate meets Amazon's high hiring bar. Expect a mix of technical and behavioral questions.

Amazon Business Intelligence Engineer (BIE) Interview Questions

To excel in the technical interview, start by reviewing and brushing up on the core concepts and tools commonly used in the field of business intelligence engineering.

Studying for the BIE Interview

Focus on topics such as SQL, Data Analytics, ETL tools, Data Visualization, Statistics, Python, and Tableau/Quicksight or other similar tools. Apart from this work on solving analytical problems under time constraints. Practice coding exercises, data manipulation challenges, and case studies to enhance your problem-solving abilities.

To read more Amazon interviews follow this resource and prepare for an interview with the best chance of success.

Let’s look at some sample questions to prepare for your Amazon BIE interview:

5 SQL Interview Questions for Amazon BIE

  1. Write an SQL query to retrieve the top N products based on their total sales. Include the product name, sales amount, and any other relevant details. Assume you have a table named "Sales" with columns "ProductID," "ProductName," and "SalesAmount."
  2. Query an order table to find the total revenue by country for a given year. Break down the results by month as well.
  3. An order table contains customer IDs, order dates, product IDs, and quantities. Write a query to find the top 3 selling products overall.
  4. Given invoice tables for multiple years, write a query to find the customers with the highest lifetime spend.
  5. An inventory table has records for each product's warehouse location and quantity on hand. Write a query to identify which warehouses have less than a 1 month supply of any given product.

5 Python Interview Questions for Amazon BIE

  1. Can you provide an example of how you would use Pandas to clean and preprocess a large dataset for analysis in Amazon's data ecosystem?
  2. How would you handle missing data in a dataset using Python, and why is it important in the context of Business Intelligence?
  3. Describe a situation where you had to optimize Python code for performance. What techniques did you use, and how would you apply them to Amazon's BI tasks?
  4. Create a Python function that emulates the behavior of an SQL INNER JOIN between two lists of dictionaries. The lists represent tables, and the dictionaries represent rows.
  5. Create a Python class that maintains a rolling average of the last N numbers added to it. The class should have methods to add a new number and retrieve the current rolling average.

5 Machine Learning Interview Questions for Amazon BIE

  1. In machine learning, how would you define the bias-variance tradeoff, and why is it a critical concept when developing models for business intelligence applications at Amazon?
  2. When faced with a business problem at Amazon that requires a machine learning solution, how do you decide which type of model (e.g., regression, classification, clustering) is most suitable, and what factors influence your choice?
  3. In the context of business intelligence, how would you address the challenges posed by imbalanced datasets when developing a machine learning model, and what techniques could be employed to mitigate the impact of skewed class distributions?
  4. Explain the importance of feature selection in machine learning models for business applications. Additionally, how do you ensure the interpretability of models, especially when dealing with complex algorithms like ensemble methods?
  5. When assessing the performance of a machine learning model at Amazon, what evaluation metrics would you consider, and how do you ensure that the chosen metrics align with the business goals and requirements?

5 Statistics Interview Questions for Amazon BIE

  1. What are the different types of statistical methods and their use cases?
  2. How can statistics be used to improve business performance?
  3. Can you describe a time when you used statistics to solve a challenging business problem?
  4. What are your thoughts on the importance of experimental design in statistics?
  5. How can statistics be used to communicate complex data findings to a variety of audiences?

Amazon BIE Salary Expectations

The average salary for an Amazon Business Intelligence Engineer in the United States is $130,000 annually. Salary levels, however, might differ based on some criteria, including area and experience.

Here’s an official Amazon job search portal to apply for your next BIE job.

BIE Career growth opportunities

Amazon provides several growth opportunities for Business Intelligence Engineers. They can move up the ladder and take on roles such as Senior Business Intelligence Engineer, Principal Business Intelligence Engineer, or even a Managerial position. Apart from vertical growth, Business Intelligence Engineers can also move horizontally and take up roles such as Data Scientist, Data Analyst, or Product Manager.

A career as a Business Intelligence Engineer at Amazon can be rewarding both financially and professionally. With the right skills and experience, one can expect to climb up the ladder and take on challenging roles within the company.

What Else Amazon Interviews Cover

BTW, Amazon goes HARD on technical interviews – it's not just behavioral interviews that are a must to prepare. Check out these interactive Amazon SQL & Python interview questions:

Amazon Two Sum Python Question

You can practice more Amazon SQL interview questions here.

I'm a bit biased, but I also recommend the book Ace the Data Science Interview because it has multiple Amazon technical Interview questions with solutions in it.