10 Interview Questions and Answers on Big Data

If you want to be a big data engineer: congratulations, you’ve chosen well! This is one of the top-paying technology jobs out there, with salaries that can top $168K. But to get the big bucks, you have to make it through the interview process. That’s where we come in. Here are ten of the most common big data interview questions and answers.

10. What is big data?

This may seem like an obvious one, but it’s best to have a comprehensive answer ready just in case. It means a ton of data, of course. But the volume of data isn’t the most important factor. Instead, it’s the nature of it – that it’s of a wide variety.

9. What are the four Vs of big data?

Make sure the words volume, velocity, variety, and veracity are on the tip of your tongue. Have capsule definitions for each ready as well.

8. What’s the difference between structured and unstructured data?

This is one of the most common big data interview questions and answers. Structured data can be handled just fine by normal database systems – think stuff in rows and columns. Unstructured data is unorganized and doesn’t fit into those systems. For example, tweets and Facebook updates would be considered unstructured data. Try to avoid talking about semi-structured data unless you’re feeling particularly lucky.

7. How can big data analysis help businesses make more money?

Well, you’ve got to justify your job somehow! For this one, think like a retailer. Information you gather about your customers can help you get pricing right, have more effective sales, and introduce products people are more likely to want to actually buy.

6. How have you used data recently to help complete a project?

Examples, examples, examples! Think back to the (hopefully) recent past and find a time you used big data. Get as specific as you can about how your contribution brought something new to the table and helped the project succeed.

5. What are some challenges or problems you’ve faced in working with data?

Honesty is the best policy here. No one, not even a big data engineer, is perfect. What your prospect employer is looking for is someone who can dive headfirst into a challenging situation and come out on top.

4. What security issues should we be concerned about?

Keeping data secure is, or at least should be, a priority for every big data engineer. Make sure to do some research on the company before you walk in the door (no hacking!), and be prepared with some plausible-sounding answers about security risks they may not have thought of.

3. How do you learn new technologies?

However much recent grads might like to think otherwise, they don’t know everything. But what’s important is how you learn what you don’t know. What if you have to solve a problem in a computer language you’re unfamiliar with? Or there’s software you’ve never seen? Let your past experience guide you in answering this question.

2. What is Speculative Execution?

Big data engineers frequently work in Hadoop. Thus, you’re sure to get at least some questions about it. A Speculative Execution happens when a small part, or “task,” of whatever overall problem is being solved is running slow. Hadoop automatically makes a replica of the task and runs that as well – that is the S.E. Once one of the two versions of the task finishes, the other is deleted.

1. What is the best hardware configuration to run Hadoop?

You’ve got to know what you’re working with, and prospective employers will expect you to prove that by answering this question. The simplest, most direct way is to advocate for dual core machines or dual processors with 4GB or 8GB RAM that use ECC memory. Be aware, though, that this can change depending on circumstance, so be prepared to be flexible.