Are you preparing for an SQL interview at Amazon? Whether you are a beginner or an experienced professional, mastering SQL is essential for a successful interview for a developer or related jobs. To become an SQL developer at Amazon, you need to have a strong understanding of SQL functions, advanced commands, database design, and advanced queries. The recruiter asks questions based on these topics to evaluate your expertise in SQL and determine your suitability for the role. In this blog, we will cover a wide range of Amazon SQL interview questions and discuss the interview process to help you answer everything from general questions to technical interview questions with confidence in your next interview.
Amazon SQL Interview Process
Amazon puts candidates through a thorough evaluation process to check the database management and query optimization skills of the prospect candidate. Here are the different stages of the Amazon SQL interview process and what you can expect:
Initial Phone Interview
First, you will have an initial phone interview with a recruiter or a member of the talent acquisition team.
- Provide specific examples of SQL projects you have worked on, including details about the goals, your responsibilities, and the results.
- Explain how you have used SQL to solve problems or improve processes in previous roles.
- Focus on demonstrating your technical proficiency with SQL and your ability to apply those skills to add value and solve real-world business problems.
The next step will be the technical interview(s), which is the core part of assessing your SQL skills. You may have one or multiple rounds, each centered around SQL-related questions and problem-solving issues.
- You should brush up on SQL basics, like SELECT statements, JOINs, and GROUP BY clauses, and practice optimization techniques for complex queries.
- You should be ready to discuss your approach to real-world SQL challenges.
For some positions, the next step may be an onsite interview where you will meet with various team members, including SQL experts and managers.
- You can expect more in-depth technical questions and scenarios that assess your ability to apply SQL concepts to Amazon’s real-world data challenges.
- Be prepared to dive deeper into advanced SQL concepts like window functions, CTEs, and stored procedures.
- You must familiarize yourself with Amazon’s data structure and business scenarios, and showcase your ability to handle complex database design challenges.
Also Read: Amazon Interview Questions and Answers
Amazon SQL Interview Questions: General SQL Questions
To answer these questions properly, clear communication and critical thinking are very important. Be ready to explain your thought process and alternative approaches, and demonstrate your problem-solving skills. Here are some general Amazon SQL interview questions and answers to help you prepare.
Q1. What do you know about Amazon’s database?
Answer: Amazon relies primarily on a variety of databases to support its extensive operations. They use both relational databases like Amazon RDS and NoSQL databases such as Amazon DynamoDB. These databases play a critical role in managing customer data, and inventory, and ensuring the smooth functioning of various services across the Amazon ecosystem.
Q2. What is DynamoDB Auto Scaling?
Answer: DynamoDB Auto Scaling is a feature provided by Amazon DynamoDB, a fully managed NoSQL database service. Auto Scaling automatically adjusts the read and write capacity of a DynamoDB table in response to changes in application traffic, ensuring that the table’s performance remains optimized and meets the specified throughput requirements.
Q3. Which of the four available AWS services will you choose to collect and process e-commerce data for real-time analysis?
Answer: For real-time e-commerce data analysis, I would choose Amazon Kinesis. Amazon Kinesis enables the smooth processing of large amounts of streaming data, providing the foundation for real-time processing and analysis. The service’s scalability and integration with other AWS tools make it ideal for handling dynamic and high-throughput data streams.
Q4. Is it possible to perform a rollback after using the ALTER command?
Answer: No. Unlike other commands, in many database systems and relational databases, once the ALTER command is executed, changes are typically committed immediately, and a rollback cannot be performed to undo the alterations. So, it is important to test the ALTER statements properly before running them in production environments since you cannot simply roll them back.
Q5. Can you mention some examples of pseudo-columns in SQL?
Answer: Pseudo-columns in SQL provide additional information during query execution. Here are some examples:
- ROWNUM: Returns the row number in the result set.
- ROWID: Represents the unique identifier for a row in a table.
- CURRENT_DATE: Yields the current date.
Q6. Can you write a command to change the password of user X from “abcd” to “dfgh” in MySQL?
Answer: Here is the command to use in MySQL.
SET PASSWORD FOR 'x'@'localhost' = PASSWORD('dfgh');
Q7. At the column level, which constraint is the only one that functions?
Answer: The only constraint that works at the column level is the CHECK constraint. This constraint specifies a condition that each row in a table must satisfy.
Q8. Can you explain SQL to a person with no technical knowledge?
Answer: SQL (Structured Query Language) is a language used to communicate with databases. Imagine a large electronic filing cabinet where data is stored. SQL is the tool that helps you ask questions and retrieve, insert, update, or delete information from this cabinet. It helps in managing and interacting with data easily.
Technical SQL Questions for Amazon Interviews
With technical questions, the interviewers aim to evaluate the candidates’ understanding of advanced SQL concepts. While answering these questions, you should focus on exhibiting your technical knowledge as well as showcasing analytical skills and problem-solving abilities. Here are some technical Amazon interview questions on SQL:
Q9. Can you find the top three products with the highest average review rating for the past month?
Answer: To find the top three products with the highest average review rating for the past month, I would typically use a query like the following in SQL.
SELECT product_id, AVG(review_rating) AS avg_rating
WHERE review_date >= CURRENT_DATE - INTERVAL '1' MONTH
GROUP BY product_id
ORDER BY avg_rating DESC
Q10. Write a query to identify customers who placed at least two orders in the last quarter but have not purchased anything in the current month.
Answer: I would use the following query to identify customers who placed at least two orders in the last quarter but have not purchased anything in the current month.
WHERE order_date > DATE_TRUNC('quarter', CURRENT_DATE) - INTERVAL '3 month'
AND order_date < DATE_TRUNC('month', CURRENT_DATE)
GROUP BY customer_id
HAVING COUNT(*) >= 2
AND NOT EXISTS (
WHERE customer_id = orders.customer_id
AND order_date >= DATE_TRUNC('month', CURRENT_DATE)
Q11. How would you improve the performance of a query that frequently filters orders by a specific date range?
Answer: I would improve the performance of a query that frequently filters orders by a specific date range by following the following strategy.
- First, I would create an index on the order_date column.
- Next, I would utilize query partitioning if the table is large and partitioned by date.
- Finally, I would materialize a view with pre-aggregated data for the frequently queried date.
Q12. What experience do you have with handling missing data in a query?
Answer: I always try to make queries as efficient as possible. One good practice that I follow is to use ISNULL or COALESCE functions to replace missing values with default values. When necessary, I filter out rows with missing data, but it’s important to document any limitations or biases this might introduce.
Q13. Can you explain the concept of data normalization and its benefits?
Answer: Data normalization is a process that minimizes redundancy and ensures data integrity by storing data in atomic units without repetition across tables. This improves data consistency, reduces storage requirements, and facilitates efficient data manipulation.
Q14. What are the advantages of using stored procedures in SQL?
Answer: Stored procedures in SQL offer numerous advantages. They enhance code reusability, improve performance by reducing network traffic, provide better security control, and simplify complex queries. Additionally, stored procedures facilitate maintenance and debugging, ensuring efficient management of database operations and enhancing overall system performance.
Q15. What are the benefits of using window functions?
Answer: Window functions allow us to perform calculations on a specific set of rows within a defined window. This means we can easily calculate things like rolling averages, row ranking, etc, without the need for subqueries. With window functions, we can quickly gain insights into our data and make informed decisions with ease.
Amazon Interview Questions Based on Functions in SQL
Understanding how to use SQL functions efficiently is key to performing data analysis and generating meaningful insights. Here are some questions based on essential SQL functions commonly covered in Amazon interviews along with sample answers:
Q16. How Will you create a function to identify orders within the past week in a specific country?
CREATE FUNCTION recent_orders(country VARCHAR(2), days_back INTEGER DEFAULT 7) RETURNS TABLE
RETURNS SELECT *
WHERE order_date >= DATE_TRUNC('day', CURRENT_DATE) - INTERVAL days_back day
AND country = country;
Q17. Write a function to return the top n products with the highest total sales for a given date range.
CREATE FUNCTION top_selling_products(date_from DATE, date_to DATE, top_n INTEGER DEFAULT 10) RETURNS TABLE
RETURNS SELECT product_id, SUM(order_quantity * price) AS total_sales
WHERE order_date >= date_from AND order_date <= date_to
GROUP BY product_id
ORDER BY total_sales DESC
Q18. How will you design a function to check if a customer has placed any orders in the past month?
Answer: I will design a function to check if a customer has placed any orders in the past month, by using the following SQL syntax:
CREATE FUNCTION has_recent_orders(customer_id INT) RETURNS BOOLEAN
DECLARE last_month DATE DEFAULT DATE_TRUNC('month', CURRENT_DATE) - INTERVAL 1 month;
RETURN EXISTS (
WHERE order_date >= last_month
AND customer_id = customer_id
Q19. Can you build a function to calculate the average rating for a specific product, excluding reviews from specific users?
Answer: I will use the following SQL syntax to build the said function:
CREATE FUNCTION avg_rating_excluding(product_id INT, excluded_users VARCHAR(255)) RETURNS DECIMAL(2,1)
DECLARE excluded_list VARCHAR(255);
SET excluded_list = ',' CONCAT excluded_users CONCAT ',';
RETURN CAST(AVG(stars) AS DECIMAL(2,1))
WHERE product_id = product_id
AND user_id NOT IN (excluded_list);
Q20. Implement a function to find customers who purchased both product A and product B within the same order.
CREATE FUNCTION bought_both_products(product_a INT, product_b INT) RETURNS TABLE
RETURNS SELECT DISTINCT customer_id
WHERE order_id IN (
WHERE product_id = product_a
AND product_id = product_b;
Q21. Can you create a function to identify orders with missing shipping information?
CREATE FUNCTION missing_shipping_info() RETURNS TABLE
RETURNS SELECT order_id
WHERE shipping_address IS NULL OR shipping_city IS NULL OR shipping_postal_code IS NULL;
Q22. Design a function to calculate the discount percentage for an order based on its total amount and a promo code.
CREATE FUNCTION apply_discount(order_amount DECIMAL(10,2), promo_code VARCHAR(20)) RETURNS DECIMAL(10,2)
DECLARE discount_percentage DECIMAL(2,1) DEFAULT 0.0;
-- Get discount percentage logic for promo code here (e.g., from a separate table)
SET discount_percentage = ...;
RETURN order_amount * (1 - discount_percentage / 100);
Q23. Write a function to find the most popular product categories among customers who also purchased a specific product.
CREATE FUNCTION popular_categories_with(product_id INT) RETURNS TABLE
RETURNS SELECT category_id, COUNT(*) AS purchase_count
SQL Advanced Command Question Asked in Amazon Interview
Amazon interviews include advanced SQL commands to assess your ability to handle complex data scenarios. As a tech giant dealing with vast datasets, Amazon seeks individuals who are proficient in advanced SQL. Here are some advanced commands for Amazon SQL interview questions:
Q24. How can you optimize a slow-running query?
Answer: To optimize a slow-running query, I would consider the following strategies:
- Analyzing the query plan to identify bottlenecks.
- Considering index relevant columns.
- Utilizing appropriate join methods and query structures.
- Pre-aggregating data in materialized views for frequently used calculations.
- Partitioning large tables for efficient data retrieval.
Q25. Write a query to find the top five customers with the highest total spending in the past year, excluding orders placed on specific holidays.
SELECT customer_id, SUM(order_amount) AS total_spending
WHERE order_date >= DATE_TRUNC('year', CURRENT_DATE) - INTERVAL '1 year'
AND order_date NOT IN (
GROUP BY customer_id
ORDER BY total_spending DESC
Q26. Can you explain the concept of window functions and give an example of how you would use one?
Answer: Window functions perform calculations on a set of rows within a defined window. You can define the aspect of the window such as previous N rows or current partition. For example, to calculate rolling average sales for each product over the past 6 months, you can use the AVG and OVER functions. The AVG function would calculate the average and the OVER function would define the window of rows (6 month period) to consider for each calculation.
Q27. How would you handle missing data in a query?
Answer: I would use the COALESCE() function to replace NULL values with a default or placeholder value. Alternatively, I might employ conditional statements like CASE WHEN to handle missing data gracefully, provide meaningful substitutes, or handle the absence of data appropriately in the query results.
Q28. Briefly describe the ACID properties of transactions in SQL.
Answer: ACID (Atomicity, Consistency, Isolation, Durability) properties to ensure the reliability of database transactions. Atomicity guarantees that a transaction is treated as a single unit. Consistency maintains the database in a valid state. Isolation prevents interference between concurrent transactions. Durability ensures that committed transactions persist even in the face of system failures.
Q29. Explain the difference between CTEs and subqueries.
Answer: Common Table Expressions (CTEs) and subqueries are used for recursive and non-recursive tasks, respectively. CTEs enhance readability and can be referenced multiple times in a query. Subqueries are nested queries providing data for the main query. CTEs are more versatile for complex, reusable logic, while subqueries are simpler and often used for specific, one-time tasks.
Q30. How Will you transform row values into columns to display sales by product and month?
Answer: I would use the PIVOT clause in SQL. For example:
SELECT * FROM (
SELECT product_id, EXTRACT(MONTH FROM sale_date) AS month, sales
) AS SourceTable
SUM(sales) FOR month IN (1 AS Jan, 2 AS Feb, ..., 12 AS Dec)
) AS PivotTable;
Q31. How Will you extract specific information from a JSON column in the ‘orders’ table?
Answer: I would use JSON functions. For example, to retrieve the product name from the ‘order_details’ JSON column:
SELECT order_id, customer_name,
order_details->>'$.product_name' AS product_name
WHERE JSON_EXISTS(order_details, '$.product_name');
SQL Database Design Interview Questions for Amazon Interview
Amazon’s database design interview questions are crucial as they assess a candidate’s ability to structure, organize, and optimize databases. Here are Amazon interview questions on SQL database design:
Q32. How would you design the database to be fault-tolerant and prevent data loss?
Answer: I would follow the following strategy:
- Back up the database regularly to Amazon S3.
- Use Amazon Aurora for a highly available database service.
- Implement disaster recovery plans.
Q33. How would you monitor the performance of the database?
Answer: I would use tools like Amazon CloudWatch and database-specific monitoring features. Regularly analyzing metrics such as query execution times, resource utilization, and error rates helps identify bottlenecks. I would use periodic reviews, query optimization, and adjusting database configurations to ensure optimal performance and scalability.
Q34. How would you secure the database?
Answer: I would employ security measures like encryption at rest and in transit, access controls using IAM roles, and regularly rotating credentials. By Implementing network security protocols, such as VPCs and security groups, and conducting regular security audits, I would enhance the database’s resilience against potential threats.
Q35. How would you Migrate data from an existing database to the new Amazon database?
Answer: I would use AWS Database Migration Service (DMS) for seamless replication. I’d plan the migration, create a replication instance, and configure endpoints. During the migration, I would monitor progress and validate data consistency, ensuring a smooth transition while minimizing downtime.
Q36. How would you keep the database schema up-to-date as the requirements of the marketplace feature change?
Answer: I would keep the database schema up-to-date as the requirements of the marketplace feature change by using version control for the database schema. Then I would implement a migration plan for rolling out schema changes.
Q37. How would you measure the success of the database design?
Answer: I would monitor key performance indicators like query execution time, database uptime, and user satisfaction. I would also regularly review the database design and make changes as needed.
Advanced SQL Queries Questions for Amazon Interview
These questions will reveal your understanding of advanced concepts like window functions, materialized views, and data warehousing. Here are some advanced SQL query interview questions:
Q38. Find the top 3 customers with the highest total spending in the past year, excluding orders placed during specific promotional periods.
Answer: I would use a query similar to the following (assuming a table structure with orders and customers):
WITH CustomerSpending AS (
SUM(o.order_amount) AS total_spending
orders o ON c.customer_id = o.customer_id
o.order_date >= CURRENT_DATE - INTERVAL '1' YEAR
AND o.promotional_period NOT IN ('specific_promotion1', 'specific_promotion2')
Q39. Calculate the rolling average of daily sales for each product over the past 30 days, using window functions.
SELECT product_id, order_date, SUM(order_amount) AS daily_sales,
AVG(SUM(order_amount) OVER (PARTITION BY product_id ORDER BY order_date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW)) AS rolling_average
WHERE order_date >= DATE_TRUNC('day', CURRENT_DATE) - INTERVAL '29 day'
GROUP BY product_id, order_date
ORDER BY product_id, order_date;
Q40. Write a recursive CTE to find all descendants of a specific category in a hierarchical category table.
WITH RECURSIVE category_tree AS (
SELECT category_id, parent_id
WHERE category_id = <specific_category_id>
SELECT c.category_id, c.parent_id
FROM categories c
INNER JOIN category_tree t ON c.parent_id = t.category_id
Q41. Design a materialized view to improve performance for frequently used aggregate calculations on a large table.
Answer: I would begin by choosing a table and identifying its frequently used aggregate queries. Then, I would create a materialized view that pre-calculates these aggregates on a specific refresh schedule, optimizing subsequent queries that rely on them.
Q42. Explain the benefits and trade-offs of using partitioning on large tables.
Answer: Its benefits include faster query execution, improved storage efficiency, and easier data management. However, it adds complexity and requires careful planning for optimal performance.
Q43. How would you design a data warehouse schema for a specific business need like analytics or reporting?
Answer: I would design a star schema for the data warehouse, with a central fact table storing key business metrics and dimension tables providing context. This ensures efficient analytics and reporting, allowing users to easily navigate and analyze data.
Q44. How would you calculate the rolling average of daily sales for each product over the past month?
Answer: I would use a window function and specify a window of the past month. Assuming a table structure with sales_data:
AVG(sales) OVER (PARTITION BY product_id ORDER BY sale_date ROWS BETWEEN 29 PRECEDING AND CURRENT ROW) AS rolling_avg
sale_date >= CURRENT_DATE - INTERVAL '1' MONTH
Q45. How will you identify customers who purchased both product a and product b within the same order, excluding promotions?
Answer: I would use a query like the following (assuming a table structure with orders and order_details):
COUNT(DISTINCT product_id) AS unique_products_purchased
product_id IN ('A', 'B')
AND order_id NOT IN (
WHERE product_id NOT IN ('A', 'B')
OR promotional_order = 'Yes'
COUNT(DISTINCT product_id) = 2;
Preparing for an SQL interview at Amazon requires a strong understanding of SQL concepts, functions, advanced commands, database design, and advanced queries. By mastering these topics with the help of Amazon SQL interview questions and answers, you can demonstrate your expertise and increase your chances of success.
Did we answer all of your questions? Do let us know in the comments section below.
You can also check out our online SQL course to practice writing SQL queries, familiarize yourself with different functions and commands, and gain hands-on experience with database design tools.