Amazon Business Analyst Interview Guide

This guide focuses on interviewing for the L5 and L6 levels, but it also applies to other levels.

tl;dr

If Amazon had a love language, it would be data. Mountains of it. Petabytes pouring in every minute from clicks, carts, streams, and smart speakers.

Born as an online bookstore in the 90s, Amazon doesn’t just use data; it swims in it and builds billion-dollar decisions on top of it. From predicting what you’ll buy next to fine-tuning delivery routes down to the last driveway, it’s all about turning real-world mess into actionable business insights. Sure, Amazon is an everything store, but more than that, it’s a data company disguised as a retail, cloud, entertainment, and logistics goliath.

The company’s whole personality can be written in queries, dashboards, and models, and this is exactly where the business analysts step in. Business analysts at Amazon play part detectives, part builders, and part storytellers. They dig into data to uncover what’s working well, what’s broken, and where things can be better. They write SQL queries for automations, design visualizations, and develop data pipelines that drive decision-making and process improvement.

At Amazon, the culture runs on the infamous Leadership Principles. Business analysts are expected to “Dive Deep” (way deeper than surface-level dashboards), “Think Big” (because small ideas don’t scale), show “Ownership” (treat every problem like it’s your name on the door), and have a serious “Bias for Action.” Amazon is fast and experimental, and it rewards those who love to roll up their sleeves and let the data lead the way.

What does an Amazon Business Analyst do?

Amazon Business Analysts act as data translators, responsible for converting heaps of data into actionable business insights. That said, the complexity of research and skills for a business analyst goes well beyond basic data entry and extraction. It involves designing and developing automated data pipelines, sophisticated analytical modeling, and intuitive data visualization. They also maintain front-end code using Python, SQL, HTML, Java, and R, or other similar coding languages.

Business analysts work in teams like Listing Analytics, Amazon Transportation Services (ATS), Selling Partner Experience (SPX), Amazon Devices, AWS Global Sales, Workforce Solutions, and Trade Strategy, among others.

Irrespective of the team, here’s what a business analyst works on:

• Data access and management: Provide data management processes such as accessing raw data feeds, building queries and macros, writing VBA code, organizing data, and designing reports that present visualizations for business performance.
• Data analysis: Retrieve and analyze large sets of data using Excel, SQL, and other data management systems.
• Reporting ownership: Design and implement reporting solutions to enable stakeholders to manage the business and make effective decisions. Take ownership of reporting processes to ensure that each report is accurate and timely, with a high degree of customer focus in resolving data discrepancies.
• Tracking metrics: Build and manage key performance indicators (KPIs) to measure, control, and benchmark reporting processes. Monitor metrics, build new metrics, and partner with internal teams to identify process and system improvement opportunities.
• Cross-functional collaboration: Support cross-functional teams in the day-to-day execution of the existing program implementation.

Before you apply

• Ace Amazon’s behavioral interview questions with Exponent’s Amazon Leadership Principles course.
• Practice with our Top Amazon Business Analyst Interview Questions.

Interview process

Amazon’s Business Analyst (BA) interview process is thorough. While specifics can vary depending on the team and level, the typical interview loop includes a total of 6–8 conversations, structured like:

• Round 1: Online assessment
• Round 2: Recruiter phone screen
• Round 3: Technical phone screen
• Final onsite loop, aka Super Day, includes 5 rounds, out of which four are focused on specific Leadership principles, and one is a technical-cum-behavioral skills round.

All rounds are one-on-one and can be in-person or virtual, depending on the candidate’s location and role specifics. Virtual interviews are hosted on Amazon Chime.

Round 1: Online assessment screen

Post resume screening, the first step is a 60-minute online assessment. This typically includes 20–25 questions on SQL, Excel, and analytical skills, ranging from basic to advanced difficulty. Candidates are expected to answer at least 16 questions correctly within that time. During the assessment, SQL query writing tasks are tested in a live coding environment where the interviewer can see your keystrokes in real-time (on the internal Livecode platform, which is used by Amazon).

You may be provided with metadata such as table names, column structures, and sample data, but not a clearly defined question. Instead, you’ll have to figure out what SQL query makes sense based on the context. It’s not necessary to write the perfect query immediately; what matters more is your thought process and how you work toward a solution.

Sample questions:

1. SQL: You have a table as shown below. Find the worth of each user at the end of the month.

   Sender | Receiver | Date | Amount

• A | B | 1st May 2025 | 2000
• B | A | 3rd May 2025 | 1000
• A | C | 2nd May 2025 | 300
• C | A | 5th May 2025 | 500
• D | B | 6th may 2025 | 400

2. In SQL, if employees badged in/out to go to lunch, and badged in/out at the beginning and end of the day, how could you tell who was in the building at any given time?

Round 2: Recruiter phone screen

A run-of-the-mill recruiter screen that primarily focuses on your business analyst background and interest in the role. Be prepared to discuss the most challenging or high-impact projects you’ve worked on, as well as how you approached problem-solving and collaboration in those situations.

Recruiters may also use this opportunity to gauge your alignment with Amazon’s culture. Additionally, they will share a summary of what to expect throughout the interview process.

Sample questions:

• Why do you want to work at Amazon?
• Tell me about your past experience as a business analyst.
• What is your experience with SQL or Excel, or a specific business analytics tool?

Round 3: Technical phone screen

This 60-minute screen is usually conducted by the hiring manager and sets the baseline for technical competence. It tests you on a combination of SQL proficiency, data visualization skills, and alignment with a key Amazon Leadership Principle—often Deep Dive or Customer Obsession (which we’ll cover later in the guide). When responding to questions, make sure to use the STAR method—an approach Amazon interviewers highly value.

SQL proficiency

For this section, the interviewer will evaluate your command of key SQL concepts like:

• Joins (INNER, LEFT, RIGHT, FULL) for merging tables.
• Aggregations (SUM, COUNT, AVG) to summarize data.
• Window functions (ROW_NUMBER, RANK, LEAD/LAG) for advanced row-wise analysis.
• Common table expressions (CTEs) and performance tuning (indexing, query plan analysis, partitioning) for modular, efficient queries.

Remember that simply writing a correct SQL query won’t be enough—you need to ensure it’s optimized for performance at scale. Since every team at Amazon works with massive data sets, you must know how to adapt your query for 1 TB or even 10 TB of data.

Sample questions:

• Explain the use of GROUP BY in SQL.
• Tell me the different types of subqueries and how you use them.
• How would you find the third-highest salary in an employee table using a self-join?
• Can you write an SQL on the sales fact table and product dimension to report products with the highest revenue in each product group?
• Write a complex SQL query using Window Functions, Date, and Time.

Data visualization

You’ll be given a case study and asked to explain how you’d go about the data visualization and dashboarding process. Expect a problem statement like, “Suppose you have to recommend a product to a customer who has already filled his cart; then what data will you look for? So, how will you recommend a product to an e-commerce customer who has his cart full?”

When designing a dashboard, it's important to start by asking key clarifying questions: What type of dashboard is needed? What visualizations will best represent the data—bar charts, line graphs, heatmaps, or something else? Show that you want to understand the target audience—who will be using this dashboard, and what decisions will they make based on it? It’s also essential to consider trade-offs, such as simplicity versus depth, to ensure the final product aligns with stakeholder expectations and delivers the right insights.

The interviewer evaluates you on the following parameters:

• Do you understand how to tackle large data sets?
• Can you talk about how you want to design the underlying table?
• For the specific business scenario, would you introduce a partition or work with aggregated data, or another function?
• Do you know how to model the data in an AWS S3 or AWS Redshift database?
• Do you understand the kind of analytics you’d like for that scenario? For instance, would you propose a year-over-year trend analysis or distribution comparison, and why?
• Can you explain which chart types will best present those insights (for example, line charts for trends and box plots for variability)?

Sample conceptual questions:

• Explain how normalization helps in data analysis.
• What are the different types of data visualizations? Give examples.
• What is the difference between descriptive and predictive analytics?
• Explain how dashboards help in decision-making. Share an example of a dashboard you have created.
• How are mean, median, and mode in a positively skewed distribution related?
• What are the absolute measures of dispersion?
• How do you deal with multi-source problems?
• What is the difference between a star schema and a snowflake schema?

Final onsite loop

The Super Day at Amazon is a marathon of 4–5 interviews and may also have a bar raiser at the end. As mentioned previously, one round will focus on technical assessment, and the remaining four on different Leadership principles.

So instead of breaking down this loop by individual rounds, we’ll break it down into those two larger buckets.

Round 4: Technical and business acumen screen

This round mirrors the technical phone screen in both structure and intensity, but with an added focus on business acumen alongside SQL proficiency and data visualization skills. The candidate is presented with a real-world business problem and asked to propose a data-driven solution.

Like any other problem-solving round, there are no right or wrong answers. What matters is how you approach and define the problem statement. Be ready to ask clarifying questions, explain how you would source and prepare the relevant customer and sales data, structure the analysis (for example, segmenting by region, model, or customer demographics), and define clear success metrics. Remember to tie your final solution to the business impact.

Sample questions:

• Car sales have been declining quarter over quarter. How would you analyze this trend and identify potential root causes and recommendations?
• How will you grow Amazon’s Alexa business in a new region?
• Amazon's delivery timelines have increased over the last quarter. What factors could you investigate to identify the root cause, and how would you recommend improving delivery times?
• Amazon's refund rate for a particular product category is higher than average. What metrics would help pinpoint the reason, and how would you recommend reducing unnecessary refunds?

Rounds 5–8: Leadership Principles

Each of the remaining 4 rounds in the loop will center on 2 of Amazon’s 14 Leadership Principles. To succeed, it’s essential to prepare a story bank in advance. Think of it as a collection of strong examples drawn from recent projects, cross-functional collaborations, or analytical problem-solving efforts. In each story, be sure to highlight how you used data and analysis to guide your decisions.

For business analyst candidates, interviewers often place greater emphasis on the following principles—each of which we’ll explore in detail: Customer Obsession, Ownership, Think Big, Bias for Action, Dive Deep, and Deliver Results.

1. Customer Obsession

“Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers.”

Practice questions like:

• Describe a time when a customer asked you for one thing, but you knew that they needed something else.
• Tell me about a time when you used customer feedback to drive innovation.
• Tell me about a time you anticipated the needs of a customer.

2. Ownership

“Leaders are owners. They think long-term and don’t sacrifice long-term value for short-term results. They act on behalf of the entire company, beyond just their own team. They never say, ‘That’s not my job.’”

Practice questions like:

• Tell me about a time you did something at work that wasn't your responsibility or in your job description.
• Describe a challenging situation in which you had to step into a leadership role.
• Tell me about a time when you were dissatisfied with the status quo.

3. Think Big

“Thinking small is a self-fulfilling prophecy. Leaders create and communicate a bold direction that inspires results. They think differently and look around corners for ways to serve customers.”

Practice questions like:

• Tell me about a time when you came up with an innovative solution to a complex problem.
• Tell me about when you had to sell an idea to upper management.

4. Bias for Action

“Speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.”

Practice questions like:

• How have you convinced others to take action?
• How have you managed risk in a project?
• Describe a situation where you negotiated a win-win situation.

5. Dive Deep

“Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdotes differ. No task is beneath them.”

Practice questions like:

• How have you changed an opinion or direction using data?
• Tell me about a time when you made a decision without having sufficient data points in hand, and there was a lot of uncertainty.
• Tell me about a time when you decided based on data and were ultimately wrong.

6. Deliver Results

“Leaders focus on the key inputs for their business and deliver them with the right quality and in a timely fashion. Despite setbacks, they rise to the occasion and never settle.”

Practice questions like:

• Describe a challenging project you worked on and why it was challenging.
• Describe a situation where you negotiated a win-win situation.
• Tell me about a time you used a specific metric to drive change in your department.

Additional resources

• Get constructive feedback by practicing mock interviews with peers.
• Watch a full mock interview that includes behavioral, SQL, and analytical questions.
• Read through this analytical problem-solving case walkthrough.

FAQs about the Amazon Business Analyst interview

How should I prepare for an Amazon Business Analyst interview?

Revise and refine your SQL skills with Exponent’s SQL Interview course. Craft a customized business analyst resume review from an expert recruiter. Book a 1:1 coaching session with Amazon Business Analyst interviewers.

How much does a Business Analyst at Amazon earn?

The expected total compensation for an Amazon Business Analyst role is as follows:

• L4, Business analyst I: $93.3K
• L5, Business analyst II: $129.6K
• L6, Business analyst III: $185.7K
• L7, Principal business analyst: $318.2K

How long is the Amazon Business Analyst interview process?

The end-to-end Amazon Business Analyst interview process can take anywhere from 1–5 months from the online assessment stage to the final offer.