Age is just a number: meet Djole, the whiz kid of data engineering

Among our ranks at Content Insights, you’ll find many talents and personalities. But there is one among us who sparks particular admiration.

Despite being one of the youngest hirees here in the company, Djordje Marjanovic – a.k.a Djole – has proven time and time again that age is just a number, effortlessly standing shoulder to shoulder with his – and may they forgive the choice of wording – older colleagues. Elder colleagues. Sage. Wise-learned. Ok, boomer? 

Although you will rarely hear him brag about this, the most impressive thing from Djole’s arsenal of skills is that he is able to learn new technologies with such speed, some might say it’s sorcery. He codes, solves problems, maintains data architecture, and is also our official ping pong ninja. We say ninja because he’s so stealthy, nobody ever sees the ball after he does a backhand volley (which is something he doesn’t mind bragging about).

But the most commendable thing of all is that Djole still manages to be your down to earth kind of guy who just loves what he does.

So to teach us his ways, we decided to ask him some questions about his experience here at Content Insights, how his quest started, and how video games shaped who he is now as a data engineer.

Hail, Djole! Python has been graced by your code, but tell us a bit about yourself. When did you start dabbling in data engineering and what made you choose a career in this field?

During my university days, I was researching different types of software development with the goal of finding a career that suited me. After a few minor data science and data engineering projects, I realized I found the whole field very appealing and so I decided to run with it.

But it was not until my first job here at Content Insights – and with the help of Goran, Marko and others – that I truly immersed myself in the essence of data engineering. It’s a very exciting profession because a lot of useful stuff can be designed by using data in many different and smart ways. A lot. Basically, the sky’s the limit – and contrary to popular belief, implementation doesn’t have to consist of piles upon piles of code lines.

So how would you explain data engineering to someone who has no idea about what it actually is? 

As the name suggests, think of us as architects but with data. We design, we build, and we maintain that which has been built. Or to be more precise, we use our skills in software engineering and computer science to ensure clean, reliable, performative and uninterrupted flow of data between servers and applications. It’s a type of job that’s easy to learn but hard to master. Again, that’s just me, but considering there are a million ways to apply your data engineering skills, I feel that the only two things that truly set the best apart from the rest are creativity and simplicity. 

Interestingly enough, not only are you one of the youngest members at Content Insights, but you are well on your way to becoming one of the longest-serving. Tell us, from your perspective, what does it feel like to be such a figure in our company at such a tender age? 

Well, I don’t necessarily feel like the youngest in the company. There’s a friendly vibe at Content Insights and I have awesome colleagues, so nobody really dwells on things like age or time of service within the company. It’s a cliche, but age is just a number. I think that is one of the perks of working in startups, in general. It all boils down to your willingness to contribute, regardless of your background.

What do you find most challenging and most rewarding about working in a startup?

To be frank, I believe our parents raised us for a world that doesn’t quite exist anymore, at least if we look at Serbia, our main country of operations. With the advent of data science, the working dynamic has shifted in so many ways – and startups are leading that change. Jumping on that train definitely opens up more doors and possibilities. 

For instance, company culture is not based on hierarchy, but cooperation. Regardless if you are a C-level or entry-level position, in startups, people tend to treat each other as equals.

Most importantly, people understand that cooperation and flexibility are what keeps the wheels greased and in motion. As long as you meet your deadlines and deliver results, you are free to do your job as you please, to the schedule that works best for you.

Word is that you were offered a job just by talking to Ilija (one of our founders) during a Data Science Conference in Belgrade. You even came to the conference of your own accord. What did you guys talk about? What did you say that left Ilija with no other choice but to offer you a position at Content Insights right there on the spot? 

Actually, the story begins a few months earlier when I was still on the prowl for an internship. I knew of Ilija through members of my family, but it was not until I expressed my interest in data science that we got together to talk. We had a discussion about the company, got to know each other better and that conversation landed me a mini-project to work on as an intern.

It went really well, enough for Ilija to invite me to meet up again during the Data Science conference 3.0 (which I was planning to attend anyway). Our talk at the conference was short and simple, no more than 5 minutes. It consisted of a job offer which I accepted immediately. I believe the way I found out about CI and how I got the job was pure luck, but people have been telling me it was everything but that. 

Clearly there are more benefits for us attending these conferences that just sharing our research! How did you learn about that conference and what opportunities does it offer to aspiring coders such as yourself? 

Attending this event – and ones like it – is a terrific opportunity to hear about emerging trends in data science. I mean, the place is always swarming with curious, techy people, most of whom are dealing with coding problems and sharing experiences and ideas on how to solve them. It’s also an excellent place for job seekers to meet tech companies and hopefully even find a new job – as was the case with me. All in all, the Data Science Conference does a really good job at exposing people to the current and future trends of technology, which is particularly interesting if you see yourself working with data.

Let’s talk about your daily routine. What does your usual working day look like? 

Well, I’m not afraid to admit that I am no stranger to laziness, so the first order of business when I wake up is usually to lie around in my bed until I start feeling guilty about it. But once I’m in the office, the first thing I always do is a status check of our production and test systems. Afterward, we have a short daily meeting where we sum up what has been done so far and plan the next steps. The rest of the day is dedicated to working on these tasks – and beating colleagues at ping pong, obviously.

You’re known for being a super-fast learner. In fact, word has it that you are able to devour new technologies, find and fix bugs in open source technology and even write beautiful code simultaneously. Can you share with us what your responsibilities in Content Insights are and what you consider your special skills to be? 

The system we work on as data engineers is probably the most substantial part of Content Insights’ software, which is why its maintenance is paramount. Our system is a composite one and consists of data collection, data processing, calculations and databases. We must not allow any errors in the system and data – every part of the system has to work fast, be safe and surgically precise.

As for special skills, I don’t think I have them, but to avoid sounding too modest, I would definitely say that my forte is the design and development of the data pipeline. I feel like I’m only at the beginning of my career, so the opportunity to improve my knowledge of all programming languages and technologies here at Content Insights means the world to me. It’s a haven for us tech geeks, really. 

You look like the type of guy who is passionate about sports. Is that true? If it is, could you tell us more about that passion and which sports, in particular, do you love to play?

True. I did a lot of football training when I was younger and I still love to play it. Here at Content Insights, we often play basketball, foosball and table tennis too. To be honest, I enjoy watching virtually every sport imaginable, but most of all, I’m an avid fan of Champions League and Premier League, as well as the not-so-popular sports like snooker, rugby (but not NFL), and more. 

And what about video games? Surely someone of your caliber also appreciates a fully immersive gaming experience…?

Oh, yes! Very that. To me, video games are like books that come to life where you get to decide the fates of the characters. That whole augmented multimedia experience is what makes it so appealing. I used to play a lot of different games, mostly first-person shooters (like Call of Duty). I must commend myself for an enviable playing time of the Russian replica of World of Warcraft called Allods. Nowadays, I may not have the time to binge-play as much, but I enjoy me some FIFA, Dota 2, and PUBG with colleague Stanic and other friends. 

The older generations are – stereotypically – not so keen on video games, but the youth begs to differ. What do you think are the benefits of playing video games – and do you think gaming also contributed to where you are now as a data engineer? 

Oh, my, where do I even begin? It sharpens your motor skills. You learn English, especially if it isn’t your native language. You learn facts and history. You develop reflexes and cognitive capacities. You learn how to orient yourself and memorize things. You stimulate imagination and creativity. You plan and strategize. It all depends on the genre of the game, but I feel like every brain center can be activated with a good video game. 

I mean, gaming certainly helped with my development. It got me more into computers and later into software engineering. For instance, the recent projects I have done independently – which includes using machine learning and artificial intelligence – are based on video games, so the connection is more than obvious. For me, it’s almost necessary.

Final question: Do you have any advice or words of wisdom to impart to people who are just starting in data engineering?

Data engineering can seem like a very broad field of data science, especially if you are just starting, and that’s because, well, it is. But – seriously – don’t worry. It is only a matter of time until you find your footing, your own flow. Just stick to your own guns and keep engineering. 

Thanks to Djole for sparing some time to chat with us. If you have any additional questions about data science and data engineering, give us a shout at hi@contentinsights.com

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