Amazon Bi Engineer Interview Process- Sample Interview Questions

Amazon Bi Engineer Interview Process

Amazon is one of the leading companies across the globe. The E-commerce set up by this platform uses every latest technology like big data, data analysis, machine learning, automation, IoT, and several other technologies to leverage the existing system of the company. This constant iteration has significantly improved their performance and customer service for the last decade. Amazon continues to refine its site and provide its customers with more relevant products curated to individual needs. Here, let’s know about Amazon Bi Engineer Interview Process.

The very task of creating a curated screen condensed to individual needs is looked after by Amazon Business Intelligence engineers. The interview process for Amazon bi engineers is divided into three stages: initial screening, technical screening, onsite interview. Additional rounds can be incorporated according to the requirements.

 BI engineers work with several teams associated with the company, gathering large data into meaningful information that can be further used to improve the site. The translation of data into insights is responsible for every decision on the E-commerce platform. 

Let us dive deeper into the role of BI engineers and the necessary details regarding the interview in the further sections.

What is the role of an Amazon bi engineer?

Amazon bi engineers are primarily responsible for making business decisions. They work hand in hand with clients, data analysts, and developers to collect useful data and turn them into lucrative decisions. The business decisions made by the engineers are used for the analysis and automation of the system. Solutions retrieved from decisions are further used to iterate the site and report to the client base.

Business Intelligence engineers are often broken into several groups to look after the functioning of the entire company on different stages. This allows them to make decisions on a stepwise level, solving the problem in its nebulous stage. The roles are divided on quite a wider basis and often include solving problems through modeling the data to guide the further processes of the leaders. 

Interview process

Amazon’s interview process is categorized into 3 rounds. Initially, the recruiter reaches out via email and the 2 initial phone screenings are carried out.

Initial screening

The initial screening is divided into two phone interviews. This interview deals with technical aspects and your experience in the required field. The interviewer can also ask some behavioral questions. As a candidate, you must be ready to answer questions relating to your background and past projects to which you have contributed. 

Tips: Talk about a few significant projects you have contributed to, do not involve every single project.

Tell the interviewers the major problems that you faced in the project, how you solved them, and give a conclusion of how your contribution positively affected the decision-making. Further statistics could be included for better results, 

The second phone interview is with the hiring manager. The interview often involves questions revolving around leadership-oriented questions.

Technical screening

The technical screening round is purely based on the technical aspect of the business intelligence role. The process is carried out through a coding platform that tests the candidates on several technical aspects like SQL, Python, Machine learning, data modeling, data warehousing.

The interview will be over 30 – 40 minutes in duration. 

Tips: 

  • Get hands-on with the syntax of various languages for the interview. The coding round could involve an editor that does not detect errors thus failing to execute your code.
  • SQL is a must for the interview. Have a good command over the basics as well as the advanced concepts of the same. This would help you tackle the most difficult questions on the day of the interview.
  • During the interview, discuss the problem and give the solution to the interviewer from multiple approaches. Tell them what approach you choose and why. This will help boost your chance of selection.
  • Python has become the necessity for data modeling today, get your concepts brushed.

Onsite interview

The onsite interview is further categorized into 5 rounds of 1 hour each. The rounds are one on one interview with Business Intelligence engineers, Business Analyst, Hiring manager, and Data scientist. The 5th round is a Bar Raiser Round. 

Depending upon the range of people holding interviews, the questions can span over the expanse of data analysis, business model, situation analysis, and leadership qualities. Be ready to impress each individual, and also have your questions ready for the interviewers.

1st round: Hiring Manager

The question will be composed mostly of leadership qualities. Prepare as many scenarios of Leadership Principles as you can, also try to follow the Amazon employee policy.

2nd round: Business Intelligence Engineer.

The questions will be a mixture of Behavioral and Technical aspects. 

3rd round: Data Analyst

Purely technical round. The questions mostly revolve around data analysis, data modeling, warehousing, SQL.

4th round: Data Scientist

The round will also have a mixture of behavioral and technical questions. The round is relatively concerned with checking the basics of the person.

5th round: Bar Raiser

The Bar Raiser round is usually concerned with the leadership aspect of the company. It revolves around the Amazon 14 leadership skills. This interview is held to check your peer presence, influence, and problem-solving capabilities. Follow-up questions will be asked to dig deeper into your experience and check whether you are a fit for the role.

Tips: 

  • Don’t bluff about your experience. The interviews are designed in such a manner that they dig way deeper into the technical as well as the logical aspects of your answer. This can easily bring forward your weakness.
  • Give well-structured answers without filler content. Stick to the question and try to involve solid figures for more acceptable answers.
  • Prepare for each round as the scores are cumulated at the end. Try to give your best.

Interview questions

Now that you know about the various rounds of the interview, we have summed up a few questions from each round and a few extra questions that could help you crack the interview efficiently.

Initial screening questions

  1. Tell me about your experience when you used data to implement decisions for your project?
  2. Tell me what problems did you face while translating the data?
  3. How did you solve the problems you faced during your projects?
  4. Tell me the different aspects of data translation, and what variables you would use?
  5. Have you made some mistakes during your project? How did you solve them?
  6. What is your stand on negative feedback?
  7. How would you calculate the change in revenue on a weekly basis on Tableau?
  8. What is the difference between ETL and ELT?

Technical Screening questions

  1. State an order table, and extract queries for desired output?
  2. Code to find the palindrome of a number?
  3. Code the Fibonacci series for N recursions?
  4. How do you extract data from CSV files in python?
  5. Give me a binary tree to implement replies to customers according to their queries?

Onsite round

The questions will revolve around the following topics:

  • ETL
  • Descriptive Analysis
  • Statistical Analysis
  • SQL
  • Data Visualisation
  • Data Warehousing
  • Leadership Principles

Hiring Manager round questions

  1. Why would you like to work for Amazon?
  2. How do you handle a tight deadline?
  3. What solutions would you propose when you fall behind the deadline in a certain project?
  4. How would you help your peers in a struggling situation?
  5. What is the most constructive criticism you have received, how did you act on it?
  6. How could you contribute your best to the role?
  7. Tell me about yourself?

Business Intelligence round questions

  1. Use SQL to join two order tables?
  2. Use SQL to group and aggregate the order table?
  3. How are orders, aggregating, grouping, and outliners useful?
  4. What criteria would you use to cut the price of the product to improve sales while boosting the profit of the company?
  5. What is the most innovative idea presented by you?
  6. How will you tackle the customer obsession problems?
  7. What will be your stand in-group when you disagree with a decision and others agree?

Each question will have several follow-up questions based on the answers you give.

Data Analyst round questions

  1. Describe various design schemes in data modeling?
  2. State difference between OLTP and OLAP?
  3. Types of normalization in data modeling?
  4. Explain Windows function in SQL?
  5. How would you rank a table without using the rank table?
  6. What do you understand by SQL filtering, how is it useful?

Data scientist round questions

  1. On what criteria do you measure the success rate of your work?
  2. How would you handle disagreements within the team?
  3. Would you work if the entire team has a different opinion than yours?
  4. Design a data model for a hospital?
  5. Name the factors that would determine the success rate of a model?
  6. What factors are influential in determining product success?
  7. How would you initiate a campaign for the team to gather information about new products?

Bar Raiser round questions

  1. Why do you think you can lead a team successfully? Give an instance where you proved yourself?
  2. How would you improve the current situations of a team which are lacking in a few essential components?
  3. Have any of your plans backfired, and what did you do to solve them?
  4. What contributions would you give as a first-timer in our company?
  5. How will you solve problems when you are dissatisfied with the current project?

NOTE: 

For any question related to situational analysis try to follow the STAR methodology to solve the problem.

S – Situation

T- Task

A- Action’

R- Result

Other questions in the interview can easily range from A/B testing random model development for the analysis of certain places or situations. A piece of thorough knowledge in every domain, and expertise in few us a definite key to clearing the interviews.

BI engineer team associated with amazon

Amazon is a huge company, and this has resulted in several departments. Amazon has about 40 departments that have more than 100 subsections to look after the working of the company effectively. A BI engineer is responsible to handle the data of such a large number of teams and translate them according to the need of the hour.

BI does the job of making software that can collect the information from all the departments and easily convert them into readable and accessible data that can be further used for decision making. Based on different teams, Business Intelligence Engineers mainly perform the following task.

Payment modifications

The function of this team is related to collecting data and improving the payment experience of the customer. This also involves discounts and other offerings to the customers and provides them with required details to make the entire system user-friendly.

Care department

The team collaborates and works with different finance and business teams to find the decision-making process. This team can shape all the decisions and secure the future of the company.

Inventory Management 

The inventory management team is related to leveraging the shopping experience of the company and designing tools and technologies that could improve the shopping experience. The engineers also validate and experiment with the tools developed for the process of improvement.

Transportation Risk and Compliance

To analyze the data related to customer and partner safety, adhering to the safety protocols of the company. The team uses a machine learning model to find safety protocols and apply them in the correct aspects of the user experience. 

Logistics and analysis

The logistics and Analytics department is responsible for dealing with large and complex data available in the system of Amazon. The team works in close collaboration with the collection, mining, gathering, and curating of data. This allows the team to make recommendations and help make a profitable business decision that can streamline a positive business association.

Catalog system and organization

The team defies the business matrix that allows the company to develop service programs that define the structure of Amazon. It also allows experimentation of the data.

Required qualities for the role of BI

If you want to be a Business Intelligence Engineer in Amazon make sure you checklist the following points that could improve your chance of hiring.

  1. Have a strong analytical scheme, knowledge of data modeling and business tools.
  2. Have skills to design minimal solutions using business analytical tools like JIRA, Tableau, that emphasize customer needs.
  3. Able to handle tight deadlines and work in a fast-paced environment to keep up with the growing needs of the customer.
  4. Have adequate leadership skills to improve the business module.

How much is the pay scale?

The pay scale of Amazon bi engineer ranges from $90,812 to $158,343 per year.

To conclude, Amazon is a huge company with an extremely competitive environment when it comes to hiring. So, tighten up your shoelaces as the race is not going to be easy. But let me assure you it is going to be worth the struggle. If you have all the required skill sets and the right knowledge. Congratulations, because you are going to crack the interview. 

Amazon Bi Engineer Interview Process- Sample Interview Questions

Leave a Reply

Your email address will not be published. Required fields are marked *

Scroll to top