Landing a Business Intelligence Developer (BI Dev) role at Amazon is a dream for many data enthusiasts. But with stiff competition, nailing the interview is crucial. This guide equips you with the most relevant Amazon BI developer interview questions and expert tips to help you shine.
Securing a position as a Business Intelligence (BI) Developer at Amazon is a highly sought-after achievement. Aspiring candidates must be well-prepared for the rigorous interview process, which typically includes a series of technical questions designed to assess their skills and knowledge. In this article, we’ll explore the essential aspects of preparing for an Amazon BI Developer interview by delving into some key questions that candidates might encounter.
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Most Asked Amazon BI Developer Interview Questions
5 SQL Questions For Amazon BIE
- Query an order table to find the total revenue by country for a given year. Break down the results by month as well.
- An order table contains customer IDs, order dates, product IDs, and quantities. Write a query to find the top 3 selling products overall.
- Given invoice tables for multiple years, write a query to find the customers with the highest lifetime spend.
- An inventory table has records for each product’s warehouse location and quantity on hand. Write a query to identify which warehouses have less than a 1 month supply of any given product.
- A customer table has demographic info like age, location, date joined, etc. A separate orders table has order details. Write a query to determine the average order value for customers in different age ranges. Use joins to combine data from both tables.
5 Data Analytics Questions For Amazon BIE
- What are the different types of data analytics and their use cases?
- How would you analyze and segment customer data to better understand and target Amazon’s diverse customer base?
- Describe how you would perform cohort analysis and its potential impact on a company’s strategy. Provide a real-world example if possible.
- Can you describe a time when you used data analytics to solve a challenging business problem?
- What are your thoughts on the future of data analytics?
5 ETL tools Questions For Amazon BIE
- What experience do you have with using ETL tools in a production environment?
- Can you describe a time when you used ETL tools to solve a challenging data integration problem?
- How would you approach using ETL tools to integrate data from a variety of sources, such as a relational database, a cloud storage platform, and a web API?
- How would you use ETL tools to transform data into a format that is compatible with a data warehouse and other analytics tools?
- How would you use ETL tools to load data into a data warehouse and other analytics tools in a timely and efficient manner?
5 Data Visualization Questions For Amazon BIE
- What are the different types of data visualizations and their use cases?
- Which fundamentals are necessary for a successful data visualization?
- Can you describe a time when you used data visualization to communicate a complex data story clearly and concisely?
- How can data visualization be used to communicate outliers and anomalies in data?
- How can data visualization be used to make data more accessible and engaging for a variety of audiences?
5 Statistics Questions For Amazon BIE
- What are the different types of statistical methods and their use cases?
- How can statistics be used to improve business performance?
- Can you describe a time when you used statistics to solve a challenging business problem?
- What are your thoughts on the importance of experimental design in statistics?
- How can statistics be used to communicate complex data findings to a variety of audiences?
5 Python Questions For Amazon BIE
- Describe the variations between Python 3 and Python 2. How does Amazon’s transition to Python 3 impact Business Intelligence tasks?
- Can you provide an example of how you would use Pandas to clean and preprocess a large dataset for analysis in Amazon’s data ecosystem?
- How would you handle missing data in a dataset using Python, and why is it important in the context of Business Intelligence?
- Describe a situation where you had to optimize Python code for performance. What techniques did you use, and how would you apply them to Amazon’s BI tasks?
- Amazon’s data warehouses handle massive amounts of data. Explain how you would use Python to extract, transform, and load (ETL) this data for Business Intelligence purposes. What libraries or tools would you leverage, and why?
5 Tableau/Quicksight Questions For Amazon BIE
- Can you explain the key differences between Tableau and Amazon QuickSight? How would you decide when to use one tool over the other for a specific BI project at Amazon?
- Describe a challenging project where you used Tableau or Amazon QuickSight to create meaningful visualizations and dashboards. What was the business impact of your work?
- How do you ensure data security and compliance when sharing sensitive business intelligence reports or dashboards with stakeholders within Amazon using Tableau or QuickSight?
- In a real-time monitoring scenario, how would you use Tableau or QuickSight to track key performance indicators (KPIs) for Amazon’s e-commerce platform? What data sources and visualization techniques would you employ?
- Amazon has a massive amount of data. How do you approach data extraction, transformation, and loading (ETL) processes for Tableau or QuickSight to ensure optimal performance and accuracy in your BI projects?
Top 10 Behavioural Questions For Amazon BIE
- Can you describe a situation where you had to work under tight deadlines to complete a project or analysis?
- Tell me about a time when you faced a major challenge in a data analysis project. How did you address and get past this challenge?
- Can you provide an example of a project where you worked collaboratively with cross-functional teams to achieve a common goal in the area of business intelligence?
- Describe a situation where you had to communicate complex data or analysis findings to non-technical stakeholders.
- Can you talk about a time when you identified an opportunity to improve data quality or data governance in a previous role?
- Tell me about a project where you had to analyze large datasets to draw actionable insights.
- Can you share an example of a situation where you had to adapt to unexpected changes or shifts in project priorities?
- Describe a time when you successfully identified a recurring business problem through data analysis and implemented a long-term solution.
- Can you talk about a project where you had to make a recommendation based on data analysis, and it was met with resistance from others?
- Tell me about a time when you mentored or trained a colleague or team member in data analysis or BI techniques.
Amazon Business Intelligence Developer Responsibilities
- Design automated BI solutions for recurrent reporting (daily/weekly/monthly).
- Design data pipelines and automated processes that enable in-depth analysis.
- Design automated data validation and testing processes.
- Publish, analyze, and improve dashboards, operational business metrics decks, and key performance indicators.
Amazon Business Intelligence Developer Salary
- Base: $113k
- Stock grant: $22k
- Bonus: $27k
- Total compensation: $162k
The Amazon BIE Interview Process
The interview process for this role at Amazon consists of five main rounds:
✅ Technical Phone Screen: An essential component of the interview process for Amazon Business Intelligence Engineers is the technical interview. This round is designed to assess your technical proficiency, ability to solve problems, and comprehension of data analysis and engineering ideas. The purpose of this first 40-minute video session is to evaluate the candidate’s SQL skills, data modeling and warehousing understanding, coding prowess, and cultural fit through five to six technical and behavioral questions.
✅ Hiring Manager Screen: The focus of the second phone interview is primarily on your leadership skills and your former job issues. This is your opportunity to demonstrate your excellent decision-making and problem-solving abilities.
✅ Onsite Interviews: More emphasis is placed on your leadership skills and your past job issues during the second phone screen. This is your opportunity to demonstrate your ability to solve problems and make sound decisions.
✅ Bar Raiser Round: A full day of five interviews is to be expected, including both leadership characteristics and how you want to accomplish or surpass goals in addition to technical issues like SQL, data visualization, and ETL processes. BI engineers, managers, analysts, and data scientists will all be interviewed.
✅ Data Scientist Round: Five interviews over a full day will cover a range of technical issues, including SQL, data visualization, and ETL procedures, in addition to leadership behaviors and your approach to achieving and surpassing goals. Managers, analysts, data scientists, and BI engineers will all be interviewed.
The focus of this interview is shifted to possible commercial implications and how analytical abilities might directly improve results. Interviewers consider how you have contributed to the workplace and delve into your creative thinking, calculated risks, and data-driven problem-solving within reasonable bounds.