Interested in Apache Hadoop as a building block of your tech career? While you’re on the job hunt, Hadoop developer interview questions will explore whether you have the technical chops with this open-source framework, especially if you’re going for a role such as data engineer or B.I. specialist.

Hadoop allows firms to run data applications on large, often distributed hardcase clusters. While it takes technical skill to create the Hadoop environment necessary to process Big Data, other skill sets are required to make the results meaningful and actionable. The fast-changing Hadoop environment means that candidates should have flexibility and openness to new innovations. 

Every few years, it seems, pundits begin predicting Hadoop’s demise, killed by the cloud or some competing technology or… well, something else. But according to Burning Glass, which collects and analyzes job postings from across the country, Hadoop-related jobs are expected to grow 7.8 percent over the next 10 years. That’s not exactly dead tech, to put it mildly. Moreover, the median salary is $109,000 (again, according to Burning Glass), which makes it pretty lucrative; that compensation can raise if you have the right mix of skills and experience.  

As you can see from the below chart, Hadoop pops up pretty frequently as a requested skill for data engineer, data scientist, and database architect jobs. If you’re applying for any of these roles, the chances of Hadoop-related questions is high:

Dice Insights spokes to Kirk Werner, vice president of content at Udacity, to find out the best ways to prepare for Hadoop developer interview questions, the qualities that make a good candidate, and how practice before the interview makes perfect. 

What are the challenges faced for those specializing in Hadoop?  

Werner notes Hadoop is designed for “big, messy data” and doesn’t work well with multiple database strings.

“There’s a lot of times in tech when the buzzword is ‘the next big thing,’ and a lot of people heard Hadoop and thought they had to run all their data through these systems, when actually it’s for a lot of big, messy data,” he said. “Understanding that is the most important challenge for people to overcome—is this the right tool to use? The reality is you’ve got to understand what data you’re looking at in order to determine if it’s the right tool, and that’s the biggest thing with Hadoop.”  

When you learn Hadoop, you also learn how it intersects with a variety of other services, platforms, tools, and programming languages, including NoSQL, Apache Hive, Apache Kafka, Cassandra, and MapReduce. One of the big challenges of specializing in Hadoop is managing the complexity inherent in this particular ecosystem. 

What questions are typically asked for this position during an interview?

For Werner, it comes down a handful of fundamentals. First, there are questions that target your understanding of the terminology and what the tools can do. “How do you use Hive, HBase, Pig? Every person I talk to about the interview process, most of the questions are basic and fundamental: ‘How do I use these tools?’” 

Second, it’s key to understand how to answer a scenario-based question. For example: In a cluster of 20 data notes, with X number of cores and Y RAM, what’s the total capacity?

“Understand what they’re going to ask so you know how to work through the problem,” he said. “How do you work through the problem presented based on the tools the company is using?” Before you head into the interview, do your research; read the company’s website, and search Google News or another aggregator for any articles about its tech stack.    

It’s important to have a sense of what toolsets the company utilizes, so you don’t answer the questions completely antithetical to how they approach a particular data issue. “Practice and prepare—don’t go in cold,” Werner said. “Learn how to answer the questions, and build the communications skills to get that information across clearly. Make sure you understand the information well enough that you can go through the answer for the people in front of you—it’s a live test, so practice that.”  

What qualities make me a good candidate? 

Werner said it’s important to be comfortable with ambiguity. Even if you’re used to working with earlier versions of Hadoop-related tools, and even if you can’t fully answer a technical question the interviewer lobs at you, you can still show that you’re at ease with the fundamentals of data and Hadoop.  

“It’s about understanding machine learning in the context of Hadoop, knowing when to bring in Spark, knowing when the new tools come up, playing with the data, seeing if the output works more efficiently,” he added. “A comfort level with exploration is important, and having a logical mind is important.” 

Integrating new tool sets and distribution tools is one of the most essential skills in any kind of data work. “You have to be able to just see an interesting pattern, and want to go explore it, find new avenues of the analysis, and be more open to the idea that you might want to organize it in a different way a year from now,” Werner said.   

Why should we hire you? 

You should always spend the interview showing the interviewer how you’d be a great fit for the organization. This is where your pre-interview research comes in: Do your best to show the ways you can enhance the company’s existing Hadoop work. 

“Be honest, and don’t sugarcoat. You want to be humble, but audacious. Talk about how you add value to the organization, beyond just filling this role,” Werner said. “The interview is not just, here are the technical things we need you to know, and if you can explain how you can add broad value to your position, you’ll be much more successful. 

What questions should I ask? 

Werner advised that candidates should ask questions about team structure, including the people they’ll be working with. On the technical side of things, you’ll want to ask about the company’s existing data structures, as well as tools and distribution engines used. 

“A company’s not going to tell you the ins and outs of their data, but you’re going to want to know if they use Hive or MongoDB—they should be open about the toolsets they’re using,” he said. 

On top of that, he’s always believed asking questions prior to your interview is the best way to prepare. “It can go beyond the technology stack or database system the company has—how does the individual manage teams, what’s the success criteria for the position?” Werner said. “Show interest in what it takes to be a successful member of the team. Being prepared to be interviewed is super-important, even beyond the technical aspect of it.”