Top 15 Amazon Business Intelligence Engineer Interview Questions for 2024

Top 15 Amazon Business Intelligence Engineer Interview Questions for 2024Top 15 Amazon Business Intelligence Engineer Interview Questions for 2024

Overview

Business intelligence engineers at Amazon focus on enhancing the company’s comprehensive e-commerce platform. Data on every customer interaction is meticulously gathered and analyzed, from the moment of discovering a product to its purchase and eventual delivery. To refine site performance and improve customer experiences, Amazon integrates this data into its sophisticated recommendation system, which displays the most relevant products for each customer.

This process of creating a personalized screen of recommendations extends to all of Amazon’s products and services, including Alexa, Prime Video, and Twitch. Business intelligence engineers are tasked with translating the large data warehouse at Amazon into meaningful insights and improvements, a critical role that underscores how data drives every decision at Amazon.

Understanding this role is crucial for preparing for Amazon Business Intelligence interview questions, as it reflects the depth and scope of the skills and knowledge required for the position.

The Business Intelligence Engineer Role at Amazon

At Amazon, business intelligence engineers work with clients, analysts, and database developers to translate collected data into business decisions. The solutions created by these engineers assist in the analysis, automation, and reporting of both internal and external client data.

Frequently, Amazon engineers are embedded within teams and work cross-functionally with other teams, aiming to improve the overall customer experience. The roles of this position range from implementing solutions through data modeling to guiding business leaders.

Interview Query talked with an Amazon BI engineer about his job role and responsibilities. Here is what Amazon business intelligence engineers do:

“I ended up learning how to convert Python code to PySpark and then moved over to Amazon as a business intelligence engineer. Most of my work was around Tableau reporting, building ETL jobs, and figuring out what kind of data needed to be in the reporting databases so that your end reports work well.”

Likely when going through the business intelligence interview, you’ll be interviewing in any one of these teams.

Amazon BI Engineer

Amazon is large enough to boast of over 40 departments with more than 100 internal teams within these departments. Therefore, it is crucial for Amazon to efficiently process and analyze the huge amounts of corporate data it receives. Business Intelligence Engineers design software and corporate platforms to do exactly this, making it easier to draw meaningful conclusions from Amazon’s collected data. They work within teams and alongside Amazon’s internal clients to provide accurate and accessible data that supports critical business processes.

Based on the teams assigned, Business Intelligence Engineers may perform functions such as:

Transportation Risk & Compliance (TRC): Meticulously analyze data to find ways to keep Amazon’s customers and partners safe according to safety compliance protocols. Use predictive ML models to search for safety-related trends in the data.

Payment: Leverage huge amounts of customers’ payment data to improve the payment experience for customers. Use probabilistic models and Amazon’s technological infrastructure to display the offerings to customers in real-time.

Amazon Care: Develop data-driven models to shape the future of Amazon Care. Collaborate with business and finance teams to improve Amazon’s decision-making processes.

Automated Inventory Management: Develop analytics and prediction tools to quantify every Amazon customer’s shopping experience accurately. Work closely with Amazon’s internal customers (such as the software development team) to test and validate these tools at scale.

Logistics Business Intelligence and Analytics: Work with one of the world’s largest and most complex data warehouses. Mine data, gather customer insights, make recommendations, and help leaders make sound business decisions based on trends in data. Partner with software engineer teams to streamline or automate this business intelligence process.

Prime Video (Catalog Systems and Operations organization): Define useful business metrics, develop a self-service reporting program, and conduct experiments that can inform decisions about Amazon Prime’s Video Catalog structure.

Alexa: Use Alexa’s data source to define and automate key business metrics and leverage advanced data analytics to understand customer behavior. Design experiments (A/B experimentation) to test customer-engagement strategies.

AmazonFresh / Prime Now Customer Insights & Analytics: Use data to help Amazon better understand customers’ behavior. Develop new and innovative analysis techniques to maximize customer engagement to inform product strategy and design.

Amazon Business Intelligence Engineer Interview Process

The Amazon business intelligence interview is similar to most other technical interviews at Amazon, consisting of two initial phone interviews followed by an onsite interview.

Typically, interviews at Amazon vary by role and team, but commonly Business Intelligence interviews follow a fairly standardized process across these question topics.

Initial Screen

The initial screen is mostly a discovery interview to determine if you are a good fit for the culture and the company. The interviewer will ask you questions about your background and experience. You must be ready to discuss your past relevant projects with the interviewer. Tell them about any challenges, unique situations, or problems you faced and how you overcame them.

Onsite Interview

This is the last interview stage and comprises five one-on-one interview rounds with business intelligence engineers, data scientists, and a hiring manager. Each interview round lasts approximately 45 minutes with a lunch break in-between.

Questions in this interview span the breadth of data science concepts and are scenario-based (with real Amazon problems). Each interview round has one form of a behavioral question, and you can expect a lot of “Tell me about a time…” questions.

Overall, the onsite interview is broken down into:

  • Statistics and SQL interview with a Business Intelligence Engineer. This interview assesses your SQL and basic statistics knowledge. It also has some behavioral elements to it.
  • Behavioral interview plus SQL with some case-based questions around leadership principles.
  • Case Study Interview and behavioral interview with a hiring manager.
  • Behavioral Interview with a focus on leadership principles
  • Statistics and Product-Sense interview with a data scientist. This interview round assesses your basic knowledge of data science concepts and metric definition.

BI Engineering Interview STAR Framework

The Amazon BI interview process is designed to learn candidates’ ability to leverage data warehouse information and advanced analytics tools to turn data into meaningful information that can be used to make sound business decisions. This interview combines various data science theories, and it tests the depth of your domain knowledge as it applies to real-life situations.

Brush up on your knowledge of statistics and probability, SQL and ETL processes, and Business Intelligence solution platforms, such as Tableau, MicroDesktop, SQL SSIS, and AWS.

Also, note that Amazon asks situation-based questions, and it will help form your responses around the “STAR” format. It will also help to be familiar with Amazon’s 14 leadership principles and have a story based around these leadership principles.

STAR stands for:

  • Situation. What was the situation you or your previous employer faced?
  • Task. What tasks were involved?
  • Action. What actions did you take?
  • Results. What were the results of those actions?

Here’s an example, recently featured in The Guardian, of what it sounds like when applying the STAR Method in the interview:

Situation: “A customer rang up complaining that they’d waited more than two weeks for a reply from our sales team regarding a product query.”

Task: “I needed to address the client’s immediate query and find out what went wrong in the normal process.”

Activity: “I apologized, got the details and passed them to our head salesperson, who contacted the client within the hour. I investigated why the query hadn’t been answered. I discovered that it was a combination of a wrong mobile number and a generic email address that wasn’t being checked. I let the client know and we offered a goodwill discount on her next order.”

Result: “The client not only continued to order from us but posted a positive customer service tweet.”

We’ve gathered this data from parsing thousands of interview experiences sourced from members.

Amazon Business Intelligence Engineer Interview Questions

Practice for the Amazon Business Intelligence interview with these recently asked interview questions.

Notes and Tips:

We’ve talked to a few insiders at Amazon, and they’ve all told us that candidates most often routinely fail on the communication and business impact portion of the interview. This means not communicating how their previous work affects the business and how to work through behavioral interview questions.

While technical interview questions in SQL and Python are important, most often or not, the biggest blocker for managers to hire good business intelligence engineers is the soft skills. Practice learning how to talk about how your work translates into revenue increases or reducing costs.

See more Amazon Business Intelligence Engineer interview questions below:

Question
Topics
Difficulty
Ask Chance
SQL
Easy
Very High
Database Design
Medium
High
Machine Learning
Statistics
Easy
High

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Amazon Business Intelligence Engineer Salaries

Here’s a salary range for all business intelligence engineer roles at Amazon:

$114,408

Average Base Salary

$119,532

Average Total Compensation

Min: $73K
Max: $150K
Base Salary
Median: $117K
Mean (Average): $114K
Data points: 2,690
Min: $9K
Max: $293K
Total Compensation
Median: $100K
Mean (Average): $120K
Data points: 67

View the full Business Intelligence at Amazon salary guide

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