Ace Your SQL Interview: Dos and Don’ts That Landed Me a Job at Amazon

Landing a job as a Data Analyst, Data Engineer, BI Engineer, or Cloud Engineer often hinges on how well you perform in your SQL interview. While technical skills are crucial, they aren’t the only factor. Communication, collaboration, and problem-solving abilities play a significant role in showcasing your true potential. I’m going to break down the 3 biggest DOs and 3 biggest DON’Ts that helped me land a job at Amazon, so you can increase your chances of landing the job.

The #1 Mistake: Jumping Right In

One of the biggest mistakes candidates make is jumping straight into answering the SQL question without any preliminary discussion. It’s understandable, especially if you’ve been grinding through LeetCode problems for weeks. However, this approach can backfire. See, just hammering away at coding problems on LeetCode isn’t the same as working in a real environment.

Often, interviewers are instructed to let candidates “ramble” a bit. They want to see how you approach a problem, not just if you can regurgitate a solution. By jumping in without clarifying, you risk spending valuable time solving the wrong problem.

DO Ask Clarifying Questions: Unlocking the Real Problem

Why is it so bad to just start coding? SQL interview questions are often intentionally vague. The interviewer wants to see if you have the ability to ask clarifying questions and understand the true context of the problem. This skill demonstrates your ability to work with stakeholders and gather requirements in a real-world setting.

LeetCode practice alone won’t prepare you for this.

For example, you might be asked, “Can you write a query to analyze website traffic?” Before writing a single line of code, ask:

• What specific metrics are you interested in (e.g., page views, unique visitors, bounce rate)?
• What time period should the analysis cover?
• Are there any specific segments of users we should focus on (e.g., by geography, device type)?
• What is the desired output format (e.g., a table, a chart)?
• What database system are we using?

Asking these questions helps define the scope and objectives of the task, ensuring you’re solving the right problem. This is a great first step on how to become a data engineer.

The Pitfalls of Ignoring Hints

Sometimes, candidates ask clarifying questions but then completely ignore the interviewer’s hints. This defeats the purpose of asking questions in the first place! The point of cross-collaboration, working with other teams, and working with your stakeholder, is to listen to what they are trying to say, work in groups, and then pivot your approach.

The interviewer is likely guiding you towards a specific solution or highlighting a potential issue. Ignoring these hints can signal that you’re not receptive to feedback or collaborative.

DO Talk Out Loud: Your Thinking Process is Key

Talking out loud during the interview serves two crucial purposes. First, it can trigger you to ask clarifying questions. As you verbalize your thought process, you might realize gaps in your understanding or identify areas where you need more information.

Second, it allows the interviewer to identify if you’re going down the wrong path and offer guidance. If you remain silent, the interviewer has no way of knowing if you’re struggling or making incorrect assumptions.

Talking through your process is more important than you think!

What does “talking out loud” sound like in practice? Here are a few examples:

• “Okay, so first I need to join these two tables on the customer ID…”
• “I’m thinking of using a window function here to calculate the running total…”
• “I’m a bit unsure about how to handle null values in this column; let me think aloud about the different options…”

Remember, it’s not just about reciting code, but about explaining your reasoning and decision-making process.

How Talking Out Loud Feeds Back into Asking Good Questions

The process of talking out loud while you are working on the problem might trigger you to ask a question.

If you are explaining the work out loud and you don’t understand something, then you will easily be able to identify it and ask the interviewer for clarification.

Why the Interviewer Is On Your Side

It’s easy to feel like the interviewer is trying to trick you. The reality is that the interviewer is there to help you. They want to assess your ability to collaborate and problem-solve in a real-world setting. They aren’t trying to play games.

The Danger of Waiting Until the End to Test

Many candidates make the mistake of writing code for an extended period without testing it. This can lead to wasted time and frustration when you finally realize you’ve made a mistake somewhere along the way.

This issue, like many others, is often a result of over-reliance on LeetCode-style practice, which might not emphasize iterative testing.

DO Test Iteratively: Break Down the Problem

Instead of writing a massive query and hoping it works, break down the problem into smaller, manageable chunks. Test each chunk individually to ensure it produces the expected results before combining them into a final query.

I call this the “breaking up the question” method.

Let’s say you’re asked: “Find the revenue for the last five years broken down by category.”

Break it down:

• Find Revenue (SUM function)
• Last 5 Years (WHERE clause)
• Breakdown by Category (GROUP BY statement)

Here are example code snippets for each step to help show the process:

• Finding Revenue: SELECT SUM(revenue) FROM orders
• Last 5 Years: WHERE order_date >= DATE('now', '-5 years')
• Breakdown by Category: GROUP BY category

Test each snippet individually to ensure it produces the expected results before combining them into a final query. Highlight the importance of checking for edge cases and potential errors at each step. This is a great way to help you prepare for SQL Interview Tips For Data Engineers.

The Power of Pseudo-Code

Breaking the problem down like this facilitates the creation of pseudo-code for each step. Pseudo-code helps you plan your code and makes the coding process easier.

This can also give you an opportunity to talk out loud to the interviewer to make sure you are going down the right path, and you understand the problem.

Bonus Tip: It’s Not Just About the Right Answer

SQL interviews are graded on more than just the correctness of your final code. The interviewer is also assessing your communication, collaboration, and problem-solving skills. This ties back to the earlier points about asking questions, listening to hints, and talking out loud.

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Acknowledge 3rd Party Code Tools

It is OK if you are in an interview and want to use an AI tool like ChatGPT or Bard.

You can use tools like these to help with the code you are writing.

But you NEED to let the interviewer know that you are using it, and it can’t be used to write the full code.

If you use these tools, you need to acknowledge them in your thinking out loud process so the interviewer can understand.

Overarching Theme: Communication is Key

The overarching theme of all of this is communication. Make sure that you are communicating with the interviewer. Communication is the key to having a great interview.

The interview isn’t just about answering the question. It’s also about seeing if you’re a good fit with the team and easy to work with.

Reader Engagement: Share Your SQL Interview Mistakes

Now it’s your turn! What’s one mistake you’ve made in a SQL interview? Share your experiences in the comments below, and let’s learn from each other. I’ll do my best to provide feedback and guidance.

If you found these tips helpful, please subscribe, like, and share this post! Your support helps me create more content like this.

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Conclusion

SQL interviews are about more than just technical skills. They’re an opportunity to showcase your communication, collaboration, and problem-solving abilities. By avoiding the common mistakes outlined in this post and embracing the DOs, you can approach your next SQL interview with confidence and increase your chances of landing the job. Remember, your journey to accelerate your data analyst career starts with preparation and a strategic approach!

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