Top 22 Amazon Business Intelligence Engineer Interview Questions + Guide in 2024

Amazon’s recently published 2024 State of Procurement Data Report highlights its increased focus on operational efficiency, procurement budgets, and sustainability. Data is at the heart of solving these exciting operational challenges, and that is where the Amazon business intelligence engineer (BIE) comes in. Amazon’s BIEs translate its large data warehouses into strategic decisions.

If you’re looking for guidance to ace your interview, this guide will help you navigate every step. We’ll cover the interview process, commonly asked Amazon business intelligence engineer interview questions, our favorite tips for standing out as a candidate, and resources that Interview Query members found valuable in their preparation journey.

The Amazon BI interview process will test how you leverage data to inform strategic decisions. SQL is a core competency, and behavioral questions centered around Amazon’s Leadership Principles will be emphasized. In addition to these skills, your familiarity with statistics and probability, ETL processes, and business intelligence solution platforms will also be tested.

If you’re looking for prep strategies, check out our interview with one of our members who successfully landed a BI engineer role at Amazon. We’ve also written a guide on how to land a BI job.

The interview will be conducted in the following stages:

Step 1: Preliminary Screening

A phone interview with a recruiter will be scheduled to get a sense of your work experience and skillsets. They may also ask CV-based questions or try to find out why you want to join Amazon, so prepare some pointers to help you sail through this important step.

Step 2: Technical Interviews (Phone Screening)

Successful candidates then undergo two interviews, usually via video chat with a potential teammate or manager. These involve technical and behavioral components, focusing on Amazon’s Leadership Principles. The phone screening stage consists of 5 SQL questions (of progressively increasing difficulty) + 2 behavioral questions, although you may be asked 1 or 2 Python questions as well.

Since SQL is a core competency for BIEs, expect medium to difficult questions on window functions, complex joins, self-joins, etc.

Step 3: Onsite Interviews

Once you’ve passed the technical screening, you will be invited to spend a day at one of their offices, participating in five 55-minute interviews with managers, peers, and a senior executive. These interviews consist of SQL, Python, data visualization, and Amazon Leadership Principles-based behavioral questions. You will have a lunch break with a potential teammate between the rounds.

Step 4: Bar Raiser Interview (Optional)

Sometimes, you will be invited to a “Bar Raiser” interview, where an interviewer trained to maintain high hiring standards at Amazon will talk to you. They will focus on your holistic fitness for Amazon rather than specific team needs. Bar Raisers hold positions that are typically outside the business for which a candidate is being interviewed, and they primarily ensure Amazon’s Leadership Principles will be upheld if you are chosen. Read more about this unique interview step here.

Apart from SQL and understanding Amazon Leadership Principles, BI Engineers are expected to:

• know ETL processes and data warehousing concepts
• be skilled in data visualization
• have statistics and coding skills
• know about diverse database management systems
• be familiar with cloud platforms
• understand data security and compliance

The questions will revolve around testing these skills. Here are our top 20 questions and strategies for answering them:

1. Can you tell me about a time you had to take the lead in a challenging situation?

Amazon highly values leadership qualities—even in non-leadership roles—because employees are expected to take the initiative, especially in high-stakes situations.

How to Answer

Highlight how you motivated the team and any critical decisions you made. Show that you have an entrepreneurial mindset, can work with scarce resources, and are willing to go outside your comfort zone.

Example

“In my previous role, when our team faced a critical deadline for launching a new feature, the project lead unexpectedly had to take leave. I decided to coordinate the project’s final stages. I began by looking at our priorities again and redistributing tasks based on team members’ workloads. To keep morale high and ensure everyone felt supported, I began daily check-ins as a space for the team to share concerns and progress updates. We successfully met the deadline, and the final solution received positive feedback for its functionality and user interface.”

2. Why do you want to work with us?

The interviewer wants to know that you aren’t applying randomly and are actively interested in working for Amazon. Check their About page for more information on their guiding values and goals.

How to Answer

Start with what you admire about Amazon and how this ties in with your mission and career goals. Demonstrate that you know the company, position, and the work that the team does. Focus on Amazon’s role as a leader in innovation, its commitment to customer-centric solutions, and the opportunity to work on challenging problems at scale.

Example

“I want to work at Amazon because its business strategy of implementing AI and machine learning to solve problems at scale is a challenge that deeply motivates me. The opportunity to contribute to projects that impact millions of customers globally promises a great learning experience. I’m also drawn to Amazon’s culture of innovation and customer obsession, which aligns with my professional values and desire for impactful work.”

3. Tell me about one of your past projects.

This is an opportunity to showcase your involvement in one of the projects on your CV. It also allows them to hear the rationale behind the decisions you made during it.

How to Answer

Pick a project you’re confident about, as you can elaborate on it much better. Briefly touch upon the project’s context, its objectives, the specific role, and the skills and tools you used, focusing on those relevant to the job you’re applying for. Discuss the impact of the project, quantifying the results if possible.

Example

“In my previous role, I led a project to enhance user engagement for our mobile application. My main responsibility was to analyze user behavior data and identify patterns that indicated drop-off points. We developed a series of predictive models to forecast user actions and implemented A/B tests to determine the most effective changes. The project resulted in a 15% increase in user retention.”

4. How do you prioritize multiple deadlines?

This question is asked to test your understanding of Amazon Leadership Principles like “Ownership” and “Bias for Action.” Effectively prioritizing tasks is crucial in fast-paced environments like Amazon, where you will face multiple competing deadlines.

How to Answer

When discussing prioritizing multiple deadlines, focus on your time management, ability to assess task importance, and strategies for planning and communicating. Provide examples from past successful projects.

Example

“I would prioritize deadlines by assessing the impact of each task in line with the ‘Ownership’ principle. This means considering customer impact and long-term value. I would also employ ‘Bias for Action’ by making quick decisions on prioritization, ensuring efficient progress without unnecessary delays. Regular communication with stakeholders to align priorities and expectations would also be a key part of my approach.”

Tip: Practice more behavioral questions that test your ability to follow Amazon’s Leadership Principles. Keep a note of your past work and highlights, and find ways to quantify your impact wherever applicable. Familiarize yourself with the STAR (situation, task, action, result) method to structure your responses in a compelling way.

5. How do you resolve conflict with co-workers or external stakeholders?

The interviewer needs to know how you handle conflicts on a team, as engineers collaborate closely with other teams at Amazon.

How to Answer

Illustrate with a concise example, using it to spotlight your initiative and emotional intelligence.

Example

“In a past project, I worked with a team member who tended to make unilateral decisions and had difficulty effectively communicating their thought process.

Realizing this affected our productivity and team dynamics, I requested a private meeting with this colleague. I tried to understand their perspective while constructively expressing the team’s concerns. During our conversation, I learned that their approach came from a deep sense of responsibility and a fear of project failure. I acknowledged their commitment and explained how collaborative decision-making could enhance project outcomes.

We agreed on a more collaborative approach, with regular briefings that clearly outlined updates. This experience taught me the value of addressing interpersonal challenges head-on but with empathy. The situation improved significantly after our discussion.”

6. Every night between 7 pm and midnight, two computing jobs from two different sources are randomly started, each lasting an hour. However, when they run simultaneously, they cause a failure in some of the company’s other nightly jobs, resulting in downtime and high cost ($1000). The CEO needs a single number representing the annual cost of this problem. **Write a function to simulate this problem and output an estimated cost.

For Amazon, where efficiency and scalability are crucial, preventing such costly overlaps in job scheduling can lead to significant savings.

How to Answer

Outline a simple simulation approach using Python code. Emphasize clarity and efficiency, and mention any statistical concepts or probability theory you’ll use.

Example

“In this scenario, I would write a function to simulate random start times of the two jobs across 365 days. Each simulation would randomly assign start times within the window (7 pm to midnight) for both jobs. I would then check if the two jobs overlap. If they do, this would count as a failure event. By multiplying the number of failures by the cost associated with each failure ($1000), we could estimate the annual cost. According to my calculations, 36% of the 365 days will have an overlap, resulting in ~$131,000 lost.”

7. What would you do if you went to the office one morning and found that the traffic to Amazon.com was super low?

Consistently high traffic is essential for sales and customer engagement. This question tests your ability to quickly identify issues and apply critical thinking.

How to Answer

Outline a structured thought process and approach for diagnosing the issue. Mention the tools you’d employ. It is important to show that you can coordinate with your team and seek help when necessary, so you can also mention how you’d communicate with other members to arrive at a solution more efficiently.

Example

“I’d first confirm the veracity of the data from multiple sources to confirm that the drop is not a reporting error. Using AWS CloudWatch, I would check server status and error rates to rule out technical issues. I would then coordinate with marketing and IT to check for recent changes to the site or any promotional campaigns that could affect traffic. If the results of my inquiries remained inconclusive, I’d set up a small team to brainstorm potential scenarios and come up with multiple hypotheses.”

8. If you were tasked with designing a data warehouse for a new online retailer, how would you design the system?

Amazon does not require very high-level data modeling knowledge of its BIEs, but you may be asked questions like this to display your familiarity with data warehousing concepts. It also tells them how well you can plan for various future outcomes.

How to Answer

Begin by discussing requirements gathering (understanding the data type, volume, and business needs). Then, move on to the design phase, talking about the choice of a suitable data warehousing model (like star or snowflake schema), the importance of scalability, and data security. Also, mention the ETL processes and how you would ensure data quality and integrity.

Example

“I would start by identifying the key business questions the warehouse needs to answer and the types of data required. This includes transactional data, customer data, inventory data, etc. Based on this, I’d choose the star schema for its simplicity and effectiveness in handling typical retail queries. Scalability is critical, so I’d opt for a cloud-based solution like AWS Redshift or Google BigQuery. For ETL processes, I’d ensure that the data extraction is efficient, transformations are accurate, and loading is optimized for performance. I’d emphasize data integrity, security, and compliance with relevant data protection regulations. This approach ensures the data warehouse is robust, scalable, and aligned with business objectives.”

9. Describe a situation where you had to create a dashboard for a non-technical audience. What tools did you use, and how did you ensure the data was understandable and actionable?

BIEs need to interact with various stakeholders across the business. You’ll want to make sure insights are accessible to decision-makers regardless of their technical expertise.

How to Answer

Discuss how you chose the visualization tools and design principles you used. It’s important to talk about your business alignment, i.e., how you kept business objectives at the forefront when creating your dashboard. It would also help if you highlighted any feedback loops you incorporated to refine the dashboard further, as this demonstrates a growth mindset.

Example

“In a previous role, I was asked to create a sales performance dashboard for the marketing team. I chose Tableau mainly for its user-friendly interface. I used simple visualizations, such as bar charts for sales comparisons and line graphs for trend analysis. I included filters to allow users to view specific data segments without overwhelming them with too many data points. I also conducted a working session to walk the team through the dashboard, gather their feedback, and make adjustments.”

10. How would you analyze a dataset where you are informed that the data is noisy, volatile, and may not be fully accurate?

Demonstrating your ability to analyze noisy and potentially inaccurate data is critical as it shows that you can be scrappy and make decisions using scarce resources if needed.

How to Answer

Emphasize the importance of data cleaning, outlier detection, and smoothing techniques.

Example

“I would first clarify how the data is being used and whether this noise is unusual in the specific business case. For a volatile dataset, I’d first perform EDA and identify outliers using IQR and z-score methods. I would confer with domain experts to check if potentially suspect values are feasible. Additionally, I’d explore data smoothing techniques and anomaly detection methods to manage volatility and inaccuracies in the dataset, ensuring the analysis results are reliable and meaningful.”

11. Let’s say you are ingesting near real-time data from JSON outputs. How would you set up the process to optimize both read and write from your destination table?

Managing data ingestion and querying efficiently ensures systems remain responsive and performant under heavy loads. This will help you handle large-scale operations at Amazon.

How to Answer

Your strategy should include selecting the right data storage system, optimizing data ingestion paths, and ensuring that quick reads and writes are supported. Also, discuss partitioning and indexing strategies to optimize performance.

Example

“I would use Apache Kafka to handle the data stream because it’s scalable and can manage high throughput. Considering that we’d need efficient read and write operations, I would opt for Amazon DynamoDB for its low latency. I would further ensure that the data is partitioned correctly in DynamoDB to balance the load evenly across the shards.”

12. Given a table of bank transactions with columns id, transaction_value, and created_at representing the date and time for each transaction, write a query to get the last transaction for each day.

In a real-world scenario, you might need to extract similar insights from transactional data for daily financial summaries or end-of-day reports.

How to Answer

Focus on using a window function to partition the data. Explain the function and how the ORDER BY clause helps determine the latest transaction.

Example

“To write this query, I would use a window function like ROW_NUMBER() , partitioning the data by the date portion of the created_at column and ordering by created_at in descending order within each partition. This setup will assign a row number of 1 to the last transaction of each day. Then, I would wrap this query in a subquery or use a CTE to filter out the rows where the row number is 1. The final output would be ordered by the created_at datetime to display the transactions chronologically. This approach ensures we get the last transaction for each day without missing any days.“

13. What is the difference between OLTP and OLAP?

This question tests if you are familiar with different types of database systems and their specific uses in an Amazon business context.

How to Answer

Highlight the transactional nature of OLTP systems, emphasizing fast, atomic transactions compared to the query-intensive, analytical focus of OLAP systems. Mention some common use cases in an Amazon scenario.

Example

“OLTP (online transaction processing) systems are designed to handle large volumes of short, fast transactions. They are optimized for speed and efficiency and ensure data integrity during operations like updates, insertions, and deletions. An example could be the transaction system used in Amazon’s e-commerce checkout process.

On the other hand, OLAP (online analytical processing) systems are structured to handle complex queries for analyzing historical data. An example would be Amazon’s data warehousing solutions where data from various sources is analyzed to derive insights.”

14. We’re given a table of product purchases. Each row in the table represents an individual user product purchase. Write a query to get the number of users who bought additional products after their first purchase.

Working with user behavior data is a crucial aspect of BIE roles at Amazon. Understanding purchase patterns helps business stakeholders devise ways to enhance the user experience.

How to Answer

Explain how you would structure the query first to identify the date of the first purchase for each user and then count any subsequent purchases. Discuss the window functions you’d employ to calculate the initial purchase date for each user. Mention any edge cases, such as users who make multiple purchases on the first day—these should not count as additional ones. Once you solve the problem, mentioning edge cases exhibits your attention to detail—but solve the problem at hand first!

Example

“I’d first identify the first purchase date for each user, which could be achieved by using MIN() over the purchase date, grouped by user ID. The next step is to count any purchases after this date by filtering the main purchases table to only include records where the purchase date is greater than the first purchase date for each user.”

15. You are given two tables: Subscriptions with columns UserID, SubscriptionStart, SubscriptionEnd, and SubscriptionType and Activity with columns UserID, ActivityDate, and ActivityType. Write an SQL query to find the average number of activities per user for each subscription type, only including activities that occurred during their subscription period.

This question gauges your ability to perform complex SQL queries involving joins, date comparisons, and aggregate functions, which will be part of your daily work at Amazon.

How to Answer

Outline a strategy that involves joining the tables on UserID, filtering activities to only those that fall within the subscription period, and then grouping the results by SubscriptionType to calculate the average number of activities per user.

Example

“I’d join the tables on UserID , as this would allow us to align each user’s activities with their respective subscription periods. Next, I’d filter these joined results to include only the records where the ActivityDate falls within the SubscriptionStart and SubscriptionEnd dates.

After filtering, the data would be grouped by SubscriptionType, and for each group, I’d calculate the average number of activities using the AVG() function.”

16. We have a table representing a company payroll schema. Due to an ETL error, the employees table did an insert instead of updating the salaries when doing compensation adjustments. The head of HR still needs the salaries. Write a query to get the current salary for each employee.

Troubleshooting and fixing data quality issues will be essential to your BI engineer responsibilities at Amazon.

How to Answer

Mention the use of SQL constructs like subqueries, window functions, or GROUP BY clauses. Your explanation should demonstrate your ability to write efficient SQL queries.

Example

“To get the current salary for each employee from the payroll table, I would use ROW_NUMBER() over a partition of the employee ID, ordered by the salary entry date in descending order. This ordering ensures that the most recent entry has a row number of 1. I would then wrap this query in a subquery or a common table expression (CTE) and filter the results to include only rows where the row number is 1. This method ensures that only the latest salary entry for each employee is retrieved, correcting the ETL error that caused multiple inserts.”

17. What are the different ways to optimize queries for performance tuning?

This question is pivotal because optimization is a fundamental skill that ensures databases perform efficiently under heavy loads. Given Amazon’s massive datasets and complex queries, the ability to fine-tune query performance is essential for maintaining system responsiveness.

How to Answer

Discuss various strategies to optimize queries, including both physical and logical aspects of the database system. Explain practical techniques such as indexing, query restructuring, proper use of joins, and effective use of caching. You also need to address the importance of understanding the underlying data model first.

Example

“An effective approach is indexing. Creating indexes on columns used frequently in WHERE clauses or as JOIN keys can drastically reduce lookup times. Another strategy is to refactor queries by minimizing the use of subqueries and replacing them with joins, as joins are generally more efficient in execution. We should also make sure that the most selective filters are applied early in the query to reduce the amount of data processed in subsequent steps.

It’s also necessary to consider physical hardware aspects, such as memory and CPU, which can also impact query performance. Implementing caching mechanisms where repetitive query results are stored can also reduce load times.”

18. Let’s say you have a table with a billion rows. How would you add a column inserting data from the source without affecting the user experience?

Amazon’s vast databases require constant updates while ensuring that these changes do not negatively impact the performance of live applications.

How to Answer

Discuss strategies like batch processing, using a background process, and implementing appropriate indexing strategies. You should also mention how you would plan and test operations in a staging environment before deploying them in production.

Example

“I’d plan the operation during off-peak hours and use a staged approach, where the column is first added without any default values to avoid locking the table. Once the column is in place, I would incrementally backfill it with data using batch processing.

Post-update, it’s important to monitor for any unexpected behavior and to add necessary indexes on the new column if it’s expected to frequently be a part of query conditions. If feasible, conducting this operation in a replica of the production environment would help us solve potential issues without risking the stability of the live environment.”

19. How would you handle missing data in a dataset using Python?

This question simultaneously tests your familiarity with common Python libraries and your ability to deal with common data quality issues.

How to Answer

Explain when to use techniques like imputation, deletion, or substitution and the considerations for choosing one method over another based on the context of the analysis. Mention any additional steps for validating the results after handling the missing data.

Example

“If the data is missing at random, I might choose to simply remove those rows, especially if the dataset is large enough to remain representative. However, for smaller datasets or when the missing data is not random, I’d prefer imputation to preserve available data.

Using the pandas library, I’d implement various imputation techniques, such as filling missing values with the mean, median, or mode of the column for numerical data or the most frequent value for categorical data. For more sophisticated approaches, I might use interpolation methods or predictive modeling techniques like k-nearest neighbors.

Finally, I would perform validation checks by plotting distributions to ensure that the imputation has not altered the underlying statistical properties of the dataset.”

20. Given two tables, a users table (with demographic information) and a neighborhoods table, write a query that returns all neighborhoods that have zero users.

As a BIE at Amazon, you may need to execute similar SQL functions to optimize resource allocation and target marketing efforts.

How to Answer

Explain the logic of joining the two tables (users and neighborhoods) so that you can count the number of users in each neighborhood and then filter out those neighborhoods with zero users.

Example

“I would perform a LEFT JOIN between the users table and the neighborhoods table on the neighborhood identifier. Then, I would use a GROUP BY clause on the neighborhood identifier and a COUNT function on the users’ IDs. The key is to use a HAVING clause to filter out the neighborhoods where the count of users is zero. This approach ensures we consider all neighborhoods, even those without any associated users, and only return those with no users.”

21. Say you are given a dataset of perfectly linearly separable data. What would happen when you run logistic regression?

When applying logistic regression to a dataset of perfectly linearly separable data, the behavior of the model can be quite problematic. Logistic regression, which relies on estimating parameters using gradient descent, seeks to maximize a likelihood function.

How to Answer

Describe the impact of linear separability on the logistic regression model’s convergence. Explain that with perfectly linearly separable data, there is no tradeoff in the likelihood function; thus, the model can keep increasing indefinitely without finding a peak. Discuss the concept of regularization as a technique to address this issue, by adding a penalty term to the likelihood function to introduce the necessary tradeoff and allow the model to converge.

Example

“In scenarios where data is perfectly linearly separable, the logistic regression model may fail to converge due to the lack of a peak in the likelihood function. This occurs because the gradient ascent algorithm will continuously search for higher values without ever settling at a maximum. To mitigate this problem, regularization techniques such as L1 or L2 regularization can be applied. These techniques introduce a penalty for large coefficients, effectively creating a tradeoff that helps the model converge to a solution by preventing it from pursuing infinite slopes.”

22. Let’s say you have a time series dataset grouped monthly for the past five years. How would you find out if the difference between this month and the previous month was significant or not?

This question evaluates your ability to analyze time series data and identify significant changes while accounting for seasonality and trend effects.

How to Answer

Discuss methods to test if the difference between months is significant by examining differences in unique visitor counts. Explain the process of using a t-test on these differences to determine statistical significance. Additionally, address the need to account for seasonality and trend by adjusting data through normalization and forecasting. Highlight the importance of setting a threshold for variance based on the business context to ensure meaningful analysis.

Example

“To determine if the difference between this month and the previous month is significant, I would first calculate the differences in unique visitors between each month and the subsequent month over the past five years. I would then perform a t-test on these differences to obtain a p-value, which will indicate statistical significance if below the chosen threshold.

Considering seasonality and trends is crucial. For instance, if visitor numbers increase in summer, I’d normalize data for May through August accordingly. I would also forecast expected monthly visitor numbers and compare these forecasts with actual figures. Adjusting for trends and seasonality ensures that the significance of month-to-month changes is not influenced by underlying patterns.”

Here are some tips to help you excel in your Amazon interview:

Study Your Resume

Amazon interviews will dive deep into your previous work to understand your fit and expertise. Make sure you can quantify the impact of your projects and highlight your specific contributions within a team.

Study the Company and Role

Research Amazon’s recent news, updates, values, and business challenges. Understanding their culture and strategic goals will allow you to present yourself better and determine whether the company is a good fit for you.

Explore the specific role at Amazon through our Learning Paths to see how well your skills align with this position.

Visit Amazon’s BIE prep guide, a valuable resource for preparing for their interview.

Understand the Fundamentals

This interview will examine your SQL, analytical skills, and business acumen in depth. You will also be expected to showcase structured thinking and a curious, solution-driven mindset. For SQL, make sure you brush up on joins, lead and lag functions, pivoting, duplicate rows, and window functions. You may also be asked statistics, product sense, and data visualization questions.

You can prep further our BI interview questions, guide on business intelligence case studies, and favorite data visualization projects.

Prepare for Amazon Leadership Principles-focused Questions

Prepare stories based on challenging experiences you’ve had in previous jobs. Highlight how you applied the company’s leadership principles in these instances. Follow the STAR framework when answering these questions.

To test your current preparedness for the interview process and improve your communication skills, try a mock interview.

What is the average salary for a BI engineer role at Amazon?

The average base salary for a business intelligence engineer at Amazon is $114,408, higher than the average base compensation for a BIE role in the US, which is around $94,033.

What other companies offer positions comparable to Amazon’s BI engineer role?

You can apply for similar roles in MAANG companies. We have interview guides for Google, Apple, Meta, and Netflix.

For insights on other tech jobs, you can read more on our Company Interview Guides page.

Are there job postings for Amazon BIE roles on Interview Query?

We have multiple openings for Amazon BIEs on our job portal. Visit the portal to apply to any of these roles, or filter the list based on your location and seniority preference to apply for another desired role.

Succeeding in Amazon business intelligence engineer interview questions requires a strong foundation in SQL, Amazon’s Leadership Principles, a winning interview strategy, and extensive prep work.

Understanding Amazon’s dynamic, customer-centric culture and thoroughly preparing with both technical and behavioral questions will be instrumental to your success.

For other data-related roles at Amazon, consider studying our guides for business analyst, data engineer, data scientist, and data analyst positions in our main Amazon interview guide.

Best wishes on your journey to landing a fulfilling role at Amazon!