Amazon SQL Interview Questions — Big Tech Interviews

Leslie B.

Leslie B.

Leslie is an ex-FAANG+ writer for Big Tech Interviews and mentor. She's loves to learning new programming languages and calls Austin, TX her home.

Amazon SQL Interview Questions — Big Tech Interviews

Amazon is a company that needs no introduction. From what started out as a small e-commerce store that sold books in 1994 to becoming one of the largest employers in the world with over 41 different subsidiaries and brands.

Amazon has experienced tremendous growth since its inception and has continued to hire roles such as Amazon business analyst, data analyst, and data scientist.

Fun fact: Every two years, Amazon employees from C-suite to recent graduates spend two days working in the customer department.

The Amazon Analyst Interview Process

Whether you’re interviewing for a business analyst, data analyst, data engineer, or data scientist role, you’re probably going to have a similar interview format.

  • Leetcode, Big Tech Interviews, or Stratascratch are going to help you pass your technical screening.
  • 1 Leadership Principle = 1 Relevant SMART example.

The Amazon Tech Interview Format

Round 1: Recruiter Phone Screen

The recruiter phone screen is typically 30–60 minutes. The goal of the phone screen is to make sure you meet the basic qualifications and requirements for the job.

Types of questions to expect during your phone screen:

This sounds like a pretty standard interview process, right?

WRONG! This is a common rookie mistake.

While your interviewer needs to get these questions out of the way, they’ll also be analyzing you for a cultural fit. Make sure you’re ready to talk about the Amazon Leadership Principles at a high level.

Lastly, during this initial interview process, it’s a great opportunity to build rapport with the recruiter and pick up pieces of information as to why they’re hiring for this role.

This knowledge will help you decide which examples to use in subsequent interview rounds.

Round 2: Technical Assessment

The technical interview typically lasts from 30–60 minutes and depending on the role may include not only SQL interview questions using SQL server but also Python and data management questions.

The most common Amazon SQL Interview concepts:

Have an upcoming technical assessment? Check out our SQL playground with the latest interview questions.

Round 3: Onsite (Final round)

The final round is an all-day interview consisting of 4–5 consecutive interviews.

There are typically 1–2 technical interviews where they gauge your technical abilities with SQL and occasionally Python and there are 2–3 behavioral interviews.

Additionally, expect to be interviewed by a bar raiser, this individual will usually be a senior manager and often times from a different segment of the business.

Their primary objective is to ensure the candidates who get offers are at a minimum 50% better than the current employees at Amazon. Their emphasis is largely around behavioral and cultural fit as they believe most individuals can come up to speed with their technical skills assuming they’ve passed the initial tech screens.

This interviewer will be the decision-maker so make sure you’re prepared with examples of how you’ve demonstrated the 16 different Amazon leadership principles.

The technical interviews will be similar to the initial coding screen with a slight twist.

Expect these technical interviews to be a level deeper than your initial technical assessment.

The interviewers will be assessing your weak points from your last technical interview so make sure you’ve ironed out your weak points and are ready to ace the assessments.

Remember to speak slowly, clarify the questions, and walk them through the logic behind your solutions.

This last step is often overlooked. It’s not unheard of for someone to get an offer due to their logic, even though they might have not solved the problem correctly.

Finally, make sure to brush up on your statistics, mathematics, database management, and data engineering questions such as ETL pipelines.

The behavioral interviews will primarily focus surrounding Amazon’s 16 Leadership Principles.

It’s extremely important that you have examples for each of these principles.

Try using the STAR format to streamline your examples,

This simple framework will help you be precise and check the boxes the interviewer is looking for.

The Amazon Business Analyst Interview

Most common responsibilities of a Business Analyst:

  • Perform complex data analysis to identify opportunities to reduce cost
  • Design, develop and establish KPIs to monitor data analytics and provide strategic insights to drive growth and performance
  • Ability to perform/own reoccurring and ad-hoc business intelligence projects
  • Develop standardized metrics to evaluate and benchmark pertaining to short and long term network planning and forecasting
  • Communicate complex analysis and insights to stakeholders and business leaders, both verbally and in writing

Interview format for a Business Analyst role at Amazon

  • Round 1: Phone screen
  • Round 2: Technical interview
  • Round 3: Onsite (final round)

The main difference between the business analyst interview and other roles like data science, data analyst, or business intelligence engineer will be the focus on SQL.

A Business Analyst at Amazon must be able to perform complex data analysis leveraging business intelligence tools and SQL to identify new ways to optimize the business objectives.

It’s unlikely you’ll be expected to work with the same stack as a data scientist.

How to prepare for the Amazon business analyst interview

You should prioritize at-least 60% of your time on the behavioral aspects of the interviews such as the 16 Leadership Principles and the remaining 40% focus on the technical components such as SQL queries and database management.

For your final round, you’ll have a sequence of 4–5 rounds of interviews. Expect 1–2 technical interviews and 2–3 behavioral interviews.

Example of a Business Analyst SQL question:

SQL Question: Write a query to calculate the total time spent working out by each olympian by day of the week

The Amazon Data Analyst Interview

Most common responsibilities of a data analyst

  • Understand how to use one or more industry analytics and metrics visualization tools (e.g. Excel, Tableau/QuickSight/MicroStrategy/PowerBI)
  • Knowledgeable in a variety of methods for querying, processing, persisting, analyzing, and presenting data.
  • Good understanding of data lineage: including sources of data; how metrics are aggregated; and how the resulting business intelligence is consumed, interpreted, and acted upon by the business.
  • Strong knowledge of and experience with database querying (SQL).
  • Knowledge of statistics and experience using statistical packages for analyzing datasets, especially Excel.
  • Practical experience with any of the following tools: Tableau, Relational databases, big data, Salesforce, Python, R, Programming (ETL frameworks)

Interview format for a data analyst role at Amazon

  • Round 1: Phone screen
  • Round 2: Technical interview
  • Round 2B: Technical interview*
  • Round 3: Onsite (final round)

* Some candidates have up to 2 technical screenings before the onsite.

The data analyst interview will in a lot of ways resemble the data science interview. It’s going to be heavily focused on problem-solving, statistics, and your proficiency with languages such as SQL and Python.

Data analyst at Amazon will leverage a suite of languages such as R, Python, SQL, and must be able to support leadership by surfacing insights from complex data sets.

How to prepare for your Amazon data analyst interview

Your preparation should primarily be surrounding the 16 leadership principles, SQL queries, and database management.

For your final round, you’ll have a sequence of 4–5 rounds of interviews. Expect 1–2 technical interviews and 2–3 behavioral interviews.

Example of a data analyst SQL question

SQL Question: Write a query to return each of the following device type for the top five customers that had the hightest minutes streamed for the last 7 days in ‘JP’.

The Amazon Data Scientist Interview

Most common responsibilities of a Data Scientist

  • Research and implement statistical and ML ing techniques (e.g. Bayesian s, NLP, graph networks, optimization methods) to different applications in talent decision making
  • Providing technical/science leadership, collaborative research, and creative problem solving to drive continued scientific innovation
  • Prototype and implement highly innovative learning algorithms and prediction techniques
  • Work closely with & software engineering teams to build implementations and integrated algorithms in production systems at a very large scale
  • Constructively critique peer research and mentor juniors and engineers
  • Presenting results, reports, and insights to both technical and business leadership

Interview format for a data scientist role at Amazon

  • Round 1: Phone screen
  • Round 2: Technical interview
  • Round 2B: Technical interview*
  • Round 3: Onsite (final round)

* Some candidates have up to 2 technical screenings before the onsite.

The data scientist interview at Amazon will touch on more complex topics such as machine learning, algorithms, or designing predictive modeling processes that handle complex data.

Similar to the data analyst you’ll need to potentially know statistics, SQL, R, and Python.

How to prepare for your Amazon data scientist interview

Brush up on your window functions, practice the different types of statistical analysis in whichever language you are most comfortable with. Make sure to practice doing time series analysis and data manipulation surrounding dates and times.

Finally, behavioral questions require you to answer honestly and straight to the point; thus, ensure that you go through your resume multiple times and properly know what you have written in it.

Your preparation should primarily be surrounding the 16 leadership principles, SQL queries, and database management.

For your final round, you’ll have a sequence of 4–5 rounds of interviews. Expect 1–2 technical interviews and 2–3 behavioral interviews.

Example of data science SQL question

SQL Question: Write a query to return the product groups in the US that have no sales of any unit.

Frequently Asked Questions (FAQ):

Question: What is the typical starting salary of an Amazon Analyst?

Ranges from $73k to $94k

Question: How many rounds is an Amazon business analyst interview?

3–4 rounds. Usually, it follows this format, Phone screen > Technical assessment > Onsite.

Question: What are the skills and qualifications for an analyst at Amazon?

  • Bachelor’s degree in Business, Engineering or a related field
  • 2+ years of professional experience in analytics, business analysis, or comparable consumer analytics position
  • Advanced working knowledge of data mining using SQL, ETL, data warehouse as well as Excel
  • Demonstrated experience in preparing and executing presentations of technical and business level data

Question: What happens behind the scenes?

The hiring committee will reconvene and review the past cluster of interviews. This is when the bar raiser will be present to ensure the candidate that gets the offer is at minimum 50% better than the current staff at Amazon. During this meeting, the committee will also be deciding for the candidate that gets the offer what his/her level will be. After this step, there will potentially be a reference check, but that is typically for more senior-level roles.

What are Amazon’s 16 leadership principles?

  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.
  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.”
  3. Invent and Simplify: Leaders expect and require innovation and invention from their teams and always find ways to simplify. They are externally aware, look for new ideas from everywhere, and are not limited by “not invented here.” As we do new things, we accept that we may be misunderstood for long periods of time.
  4. Right, A Lot: Leaders are right a lot. They have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs.
  5. Learn and Be Curious: Leaders are never done learning and always seek to improve themselves. They are curious about new possibilities and act to explore them.
  6. Hire and Develop the Best: Leaders raise the performance bar with every hire and promotion. They recognize exceptional talent, and willingly move them throughout the organization. Leaders develop leaders and take seriously their role in coaching others. We work on behalf of our people to invent mechanisms for development like Career Choice.
  7. Insist on the Highest Standards: Leaders have relentlessly high standards — many people may think these standards are unreasonably high. Leaders are continually raising the bar and drive their teams to deliver high quality products, services, and processes. Leaders ensure that defects do not get sent down the line and that problems are fixed so they stay fixed.
  8. 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.
  9. Bias for Action: Speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk taking.
  10. Frugality: Accomplish more with less. Constraints breed resourcefulness, self-sufficiency, and invention. There are no extra points for growing headcount, budget size, or fixed expense.
  11. Earn Trust: Leaders listen attentively, speak candidly, and treat others respectfully. They are vocally self-critical, even when doing so is awkward or embarrassing. Leaders do not believe their or their team’s body odor smells of perfume. They benchmark themselves and their teams against the best.
  12. Dive Deep: Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdote differ. No task is beneath them.Right, A Lot: Leaders are right a lot. They have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs.
  13. Have Backbone; Disagree and Commit: Leaders are obligated to respectfully challenge decisions when they disagree, even when doing so is uncomfortable or exhausting. Leaders have conviction and are tenacious. They do not compromise for the sake of social cohesion. Once a decision is determined, they commit wholly.
  14. 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.
  15. Leaders work every day to create a safer, more productive, higher performing, more diverse, and more just work environment. They lead with empathy, have fun at work, and make it easy for others to have fun. Leaders ask themselves: Are my fellow employees growing? Are they empowered? Are they ready for what’s next? Leaders have a vision for and commitment to their employees’ personal success, whether that be at Amazon or elsewhere.
  16. Success and Scale Bring Broad Responsibility: We started in a garage, but we’re not there anymore. We are big, we impact the world, and we are far from perfect. We must be humble and thoughtful about even the secondary effects of our actions. Our local communities, planet, and future generations need us to be better every day. We must begin each day with a determination to make better, do better, and be better for our customers, our employees, our partners, and the world at large. And we must end every day knowing we can do even more tomorrow. Leaders create more than they consume and always leave things better than how they found them.

Originally published at https://bigtechinterviews.com on April 29, 2022.

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