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How to Prepare for Amazon Data Engineer Interview

Posted on 
July 13, 2021
|
by 
Team Interview Kickstart

Since its inception in 1994, Amazon has gone from being an ordinary garage space to becoming the world's largest online retailer. And without a doubt, Amazon has eased the way manufacturers and consumers from around the globe interact. Today, there are about 310 million active customers on this platform.

Amazon's system generally relies heavily on collecting and utilizing data, thereby making data engineering a lucrative job role at the company. However, acing a data engineer interview at Amazon is tough, considering that there are a thousand others like yourself applying for such positions. Therefore, it is imperative to be exceptional to pass the data engineering interview at Amazon.

That's why we've taken the time to compile answers to some of the most troubling questions related to how to prepare for a data engineer interview at Amazon.

  • What Are the Skills Needed as a Data Engineer at Amazon?
  • What Does the Amazon Data Engineering Job at Amazon Entail?
  • What Is the Amazon Data Engineering Interview Process Like?
  • How to Prepare for an Amazon Data Engineer Interview?
  • Tips on How to Crack Amazon Data Engineer Interview

What Are the Skills Needed to Become a Data Engineer at Amazon?

Data engineering is a confluence between data science and software engineering. In fact, many data engineers start as software engineers as data engineering relies heavily on programming.

Therefore, data engineers at Amazon are required to be familiar with:

Ø  Building database systems.

Ø  Maintaining database systems

Ø  Finding warehousing solutions

Customer obsession is a part of Amazon's DNA, making this FAANG company one of the world's most beloved brands. Naturally, Amazon hires the best technological minds to innovate on behalf of its customers. The company calls for its data engineers to solve complex problems that impact millions of customers, sellers, and products using cutting-edge technology.

As a result, they are extremely selective about hiring prospective Amazonians. The company requires data engineers to have a keen interest in creating new products, services, and features from scratch. 

Therefore, during the data engineer interview, your skills in the following areas will be assessed:

  • Big data technology
  • Data warehousing
  • Data modeling
  • Complex SQL
  • Mathematics (linear algebra and probability)
  • Machine learning
  • Summary statistics
  • SAS and R programming languages

Since Amazon incorporates a collaborative workspace, data engineers work closely with chief technical officers, data analysts, etc. Therefore, becoming a data engineer at this FAANG firm also requires you to have soft skills, such as collaboration, leadership, and communication skills. 

Qualifications for a Data Engineer at Amazon

  • At the time of application, candidates must be currently enrolled in or will receive a Bachelor's or Master's degree in computer science, mathematics, statistics, engineering, or any other equivalent quantitative discipline. Or, they must have graduated less than six months before applying.
  • Proficiency in at least one scripting language, such as KornShell, Java, or Python.
  • Industry experience in ETL, data warehouse solutions, and data mining.
  • Experience in at least one query language, such as PL/SQL, SparkSQL, HiveQL, SQL, DDL, Scala, or MDX.

Preferred Qualifications

  • Industry experience through technical internship(s)
  • Master's or advanced degree in a technical field
  • Proficiency in multiple query languages, scripting languages, and schema definition languages
  • Experience in big data processing technology, such as Apache Spark or Hadoop
  • Ability to write and optimize SQL queries in a business environment with complex and large-scale datasets
  • Proficiency in data visualization software, such as Tableau or AWS QuickSight, or open-source project
  • Experience in data warehouse technical architecture, ETL, infrastructure components, reporting/analytic tools, and environment
  • Capability to deal with ambiguity in a fast-paced work environment

What Does the Amazon Data Engineering Job at Amazon Entail?

As a data engineer at Amazon, one assumes the following responsibilities:

  • Designing, implementing, and automating Amazon's distributed system for accumulating and processing log events from various sources
  • Monitoring and troubleshooting data or operational issues in data pipelines
  • Driving architectural plans and implementing them for analytic solutions, reporting, and future data storage
  • Working alongside data scientists, business analysts, and other internal partners of Amazon to identify opportunities as well as problems
  • Assisting the team to troubleshoot, research the root cause of an issue, and thorough resolving any defect in the event of a problem

The company offers an array of opportunities and experiences that facilitates one's growth. Being a data engineer at Amazon allows you to push the envelope and set your career trajectory in the right direction.

What's the Amazon Data Engineering Interview Process Like?

We've collated experiences of current and former Amazon employees and studied Amazon's career website and articles to bring you an outline of the data engineer interview process at Amazon:

Round 1: Phone Screen Interview

The Amazon data engineer interview begins with a phone screen interview. In this round, the interviewer introduces you to the company and leadership principles before getting to the more technical interview.

·       The First Phone Screen

Here, the recruiter takes you through the rudiment of the job role, explaining all the necessary details to familiarize you with the job responsibilities, your prospective team as well as the company at large.

Furthermore, this process also assesses an applicant's confidence, communication skills, and fluency.

·       The Technical Phone Screen

At this stage, the interviewer or recruiter will ask you questions about your educational background, experiences, and training projects. You will also need to elaborate on your experience in data warehousing and solving complex SQL queries.

This stage is more or less talk than doing. The interviewer's aim is to decide if you actually have what it takes to advance to the next stage.

Round 2: On-site Interview

The on-site interview is made up of five separate rounds, with each round lasting an hour. All of these rounds are designed to test the abilities you claimed to have during the telephonic interview.

·       Technical round

Here, you can expect technical questions relating to database management, data warehousing, data integration, and the likes. An interviewer(s) will ask several scenario-based questions, which will require you to design a workflow. This round evaluates your expertise and technical knowledge in the line of work.

·       Debugging round

In this round, a problem is presented for you to debug and resolve. This is to test your debugging abilities and problem-solving skills.

·       Culture-based round

This is just a break, where you will join Amazonians for lunch. You will be asked cultural questions or other generic questions —nothing serious. The aim here is to break the Amazon data engineer interview monotony and help you relax.

·       Data modeling round

This round requires you to face a series of questions based on key constraints, cardinality, normalization, relationship, schema, ERD, entity, data model, and join, among others. It can also include some theory-based questions and/or solvable queries.

·       Complex SQL round

To become a full-fledged data engineer at Amazon, you must have the ability to break down a complex problem and resolve it with SQL queries. Here, you are required to solve complex questions based on group clause, aggregate functions, subqueries, joins, etc.

Note: During these rounds, you can also expect a few behavioral questions along with the tech questions. We’ve covered a few examples and tips on how to answer them in the upcoming sections.

How to Prepare for Amazon Data Engineer Interview?

Knowing that Amazon Data Engineer's interview process is quite a tasking one, you must equip yourself with all the necessary programming and communication skills.

Before digging into the technical topics asked at an Amazon data engineer interview, you can reach out to your point of contact and understand the skills/subjects you will most likely discuss. 

Generally, to crack an Amazon data engineer interview, one must be literate in programming languages used for building data pipelines, developing data warehousing solutions, and statistical analysis and modeling.

Technical Topics to Prepare for Amazon Data Engineer Interview

  • Database systems (NoSQL and SQL)
  • ETL tools
  • Database design 
  • Machine learning
  • Data warehousing solutions
  • Java, Python, and Scala programming languages
  • Data APIs
  • Data architecture and  big data technologies
  • The basics of distributed systems
  • Data structures and algorithms
  • Data filtering and optimization

This may seem like a relatively long list of topics to prepare.

Remember — interviewers at Amazon Data Engineer interviews will not evaluate your ability to memorize all the details for each topic. Instead, they will assess your ability to apply the knowledge to solve problems effectively and efficiently. 

Amazon wields technology to improve every aspect of its customer experience. Therefore, while reviewing the above topics, ensure that you keep Amazon's customers at the top of your mind.

Examples of Tech Questions Asked at an Amazon Data Engineering Interview

Basic questions:

  • Name some of the design schemas used for performing data modeling.
  • Highlight the differences between structured and unstructured data.
  • What is a NameNode in HDFS?
  • What are some components of Hadoop?
  • Can you name the four Vs of Big Data?
  • In HDFS, what do you mean by Block and Block Scanner?
  • How can a Block Scanner handle a file that is corrupted?
  • Highlight how NameNode communicates with DataNode.
  • Explain Star Schema and Snowflake Schema in brief, and highlight their differences.

Intermediate questions:

  • Name the different usage modes of Hadoop.
  • How does Hadoop ensure data security?
  • How can Big Data Analytics contribute to increasing a company's revenue?
  • When using Hadoop, how do you calculate the distance between nodes?
  • What is Rack Awareness?
  • What is the role of Metastore in Hive?

Advanced questions:

  • Name the components in Hive.
  • What do you mean by SKEWED in Hive?
  • What does a ".hiverc file" do in Hive?
  • How do you see the structure of a database using MySQL?
  • What is the role of *args and **kwargs?
  • How can you search for a specific string in a column of a MySQL table?

Examples of Behavioral Questions Asked at an Amazon Data Engineering Interview

  • Describe a time when you faced a problem that had numerous possible solutions. What was this problem, and what was your course of action? How did you determine the course of action? What was the outcome of this choice?
  • Tell us about an experience wherein you took the lead on a project?
  • Have you ever developed a strategy by leveraging data?
  • Describe an experience where you motivated a group of individuals or promoted collaboration on a project.
  • Have you ever taken a risk, made a mistake, or failed? What was your response to this situation? Did you grow from the experience?

Books to Read to Help Prepare for Amazon Data Engineer Interview

  • “DW 2.0: The Architecture for the Next Generation of Data Warehousing” – W.H. Inmon
  • ”Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema” – Lawrence Corr
  • ”The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling” – Ralph Kimball
  • ”The Data Engineering Cookbook ” – Andreas Kretz
  • ”Learning Spark ” – Holden Karau
  • ”Spark: The Definitive Guide: Big Data Processing Made Simple” – Bill Chambers
  • ”Big Data: Principles and Best Practices of Scalable Realtime Data Systems” – Nathan Marz

Tips on How to Crack Amazon Data Engineer Interview

Learn about the company 

Before diving into the Amazon data engineer interview preparation, take some time to know Amazon as a company. You can learn about the company's customer-centricity, business teams, and the factors that make it special. Moreover, you can leverage this knowledge in the Amazon data engineer interview process.

Talk your way through your thought process

It is natural for candidates to get focused when coding or facing a schema design problem. As a result, they go silent, which makes them inscrutable to the interviewer. Although it is odd to talk your way through the problem-solving process, it is vital to do so. So, explicitly practice and develop a habit of being communicative while solving a problem.

Practice coding on a whiteboard

An on-site Amazon data engineer interview entails solving problems on a whiteboard. Therefore, if you only practice in IDEs that provide syntax support and familiar formatting, a whiteboard will seem unfamiliar and will, most likely, throw you off.

So, instead of an IDE or on paper, it is recommended that you practice writing codes on a whiteboard. This way, it will feel comfortable during the Amazon data engineer interview process. Additionally, keep the following points in mind before you head in for your Amazon data engineer interview:

  • Remember what motivates you: Be prepared to describe what motivates you about the prospective job role. Although "Why Amazon?" may seem to be a standard question, be prepared with a solid answer. Recruiters at an Amazon data engineer interview genuinely wish to know about your inspiration for exploring an opportunity with the company. Further, this also gives them a better picture of your personality. Therefore, introspect on what inspires you to pursue a career with Amazon.
  • Be concise but detailed when answering questions: However, it can be tough to gauge how much information is too much. Therefore, a way out would be to pause after succinct responses and ask if the details are enough or if the interviewer(s) want you to offer more insights.
  • Ask questions: When in doubt, do not shy away from asking questions. Follow-up when you need clarifications. At the same time, if an additional context is not given, proceed to focus on solving the problem regardless of limited information.

Learn Amazon’s STAR Technique

The STAR technique is a structured method to respond to a behavioral question through a real-life experience. Recruiters at Amazon use this technique to analyze a candidate's skills, experience, and problem-solving abilities. Therefore, the crux of this technique is to determine if you are chalked out for the job role.

Here is a rundown on the STAR technique:

Situation

First, you must describe the situation that you faced or the task that you accomplished. Remember to provide enough details for your interviewer(s) to grasp the complexities of the said situation. You can give an example from a previous job, volunteer activity, group project, or another relevant event. The key here is to be as specific as possible.

Task

Next, elucidate on the goal that you aimed to achieve. Describe your responsibility in the given situation. Perhaps you resolved a conflict with a co-worker or completed a project within a stringent deadline – make sure you highlight such an experience.

Action

Here, describe the steps you took to address the situation you described above. What was your particular contribution or the unique approach you employed to solve the problem? Frame your answer with an appropriate amount of detail. 

Result

Lastly, explain the outcomes or results generated by your action. Try to emphasize the goal accomplished and the lessons you learned on the way. Moreover, provide examples using data or metrics if applicable.

Tips to Excel at the STAR Technique

Practice applying the technique to answer behavioral questions and incorporate examples from Amazon's Leadership Principles. Wondering what these leadership principles are? Here, take a look:

  • Customer Obsession: Leaders are obsessed with their customers. They work hard to keep customer trust. While they do keep an eye on the competition, their first preference is always the customer. 
  • Invent and Simplify: Leaders invent and innovate and always find ways to simplify.
  • Ownership: Efficient leaders act on behalf of the organization. They do not sacrifice long-term value for short-term results.
  • Hire and Develop the Best: Leaders recognize exceptional talent and raise its bar with every promotion and hire.
  • Think Big: Leaders see thinking small as a self-fulfilling prophecy. 
  • Learn and Be Curious: Leaders are always curious about new possibilities and seek to improve themselves.
  • Frugality: Leaders always accomplish more with less.
  • Bias for Action: Leaders take calculated risks. 
  • Dive Deep: Good leaders operate at all levels in Amazon and stay connected to every detail.
  • Insist on the Highest Standards: Leaders have high standards and ensure that each team delivers the highest quality products, processes, and services.
  • Deliver Results: Leaders deliver timely results with the desired quality.
  • Have Backbone; Disagree and Commit: Leaders at Amazon respectfully disagree on and challenge decisions, even if it is uncomfortable.

In addition, for behavioral questions at an Amazon data engineer interview, specifics are essential. Therefore:

  • Strictly avoid generalizations. 
  • Make sure that each of your answers has a beginning, middle, and end. Moreover, you should clearly describe the situation, your actions, and the outcome.
  • Be straightforward and forthcoming. Further, when telling a story, do not embellish or omit parts of it.
  • Include drawing up short descriptions of a handful of different situations in your Amazon data engineer interview preparation.
  • Be prepared to tackle follow-up questions in detail. To gain a competitive edge over fellow candidates at the Amazon data engineer interview, you can select examples highlighting your unique skills.
  • Describe specific past experiences which demonstrate that you have taken risks, succeeded or failed, and grown in the process. 

Are You Ready to Nail That Interview?

If you’re looking for guidance and help to crack the data engineering interview at Amazon, Register for a free webinar.

As pioneers in the field of technical interview prep, we have trained thousands of software engineers to crack the toughest coding interviews and land jobs at their dream companies, such as Google, Facebook, Apple, Netflix, Amazon, and more!

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FAQs on Amazon’s Interview Process

Question 1: Is it hard to get hired at Amazon?

Amazon’s hiring process is extremely competitive. However, an individual with the required skill set, knowledge, experience, and the right prep strategy can crack an interview at this company. Moreover, applicants can opt for professional interview prep to increase their chances of being hired at Amazon.

Question 2: How many rounds are there in Amazon interviews?

Interviews at Amazon begin with a phone screening, which includes a general discussion about the role, the candidate's experience, etc., followed by a technical phone interview. Its on-site interview consists of five rounds — technical round, debugging round, culture-based round, data modeling round, complex SQL round — each lasts an hour. You can expect a few behavioral questions during each of these rounds.

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