Entering the data world to become a data practitioner might appear daunting to someone who doesn’t at least have a fundamental understanding of statistics and programming. But the sky is truly the limit when you set your mind to achieving your goal.
Ali, Iza, Piotr, and Jędrzej demonstrate this every day. Their backgrounds are in anything but data, and yet they have become integral team members at dyvenia in a very short time.
How did they achieve that? What kept them going and how did they find their motivation?
They shared their stories at dyvenia’s first event in its second season of events for data practitioners.
In the beginning, there was only determination.
Jędrzej didn’t have sufficient knowledge to be an App Developer when he applied for the position. In fact, he only had a medical diploma in his pocket; he didn’t even have a GitHub profile—a business card used in the IT world to introduce yourself to your future employer. However, Jędrzej had a huge interest in the data world and was very motivated. He was persistent in learning and growing during his earlier months and had proven himself capable as an Internal App Developer.
Ali also went through a number of sleepless nights learning about DevOps. During the day, he worked in Finance and then stayed up late studying Cloud Computing tools, such as AWS. “Patience is the key,” he shared. Patience when building infrastructure is necessary, especially if an error occurs in the system. His sleepless nights finally paid off—his two years of preparation landed him a position as Cloud DevOps at dyvenia.
The unexpected, important skill a data practitioner must possess
The unexpected thing about being a data practitioner, our guests shared, is the number of meetings one has to attend. Therefore, good communication skills are paramount. This entails the ability to explain complex technical concepts in a straightforward and comprehensible way.
Piotr Zawal, who will soon have a Ph.D. in Physics, was at the beginning of his journey at dyvenia and was quite surprised by this: “Entering the data world doesn’t mean you spend the whole day at the computer just coding.”
The communication aspect was also emphasized by Izabela Stań who has a linguistic background. As a Junior Data Analyst Team Leader, she works as a bridge between the client and the execution team. She needs to understand the client’s vision and then translate it into technical requirements for the team. Having an orthodox background allows her to look at a client’s challenge from a point of view unencumbered by industry conventions.
Ask the right questions
The evening became even more interesting when the Q&A session started. The audience was curious about the tools that the speakers used and how they should go about landing a job in the data world.
Ali had a piece of great advice for beginners concerning the dilemma of what tools they should focus on. “It is beneficial to understand some basic tools when working with data. For example, a data analyst should understand SQL, while Kubernetes is essential for DevOps, and Python for data engineers.” Then he added, “however, when the advertisement for a job requires you to be familiar with some applications—even if you only know 50% from the list of tools required, don’t be afraid to apply. If the future employer is interested in hiring you, he will adapt the role to your capabilities.”
Having a GitHub profile is a must-have to land a job in our world. Piotr developed his profile by building a project that he was interested in. Because he loves listening to music, he decided to analyze his Spotify data. In order to do that he had to understand Spotify’s API—he didn’t even know what that was when he started. “It was challenging,” he said, but because of his curiosity in this specific dataset, he managed to build a solid GitHub profile and landed the job he desired.
Iza, who is now hiring her own team members, shared that she often identified spelling mistakes in the applicants’ CVs, which is a no-go for her. Such errors speak volumes about one’s attention to detail. Furthermore, her favorite interviewing question concerns the applicant’s motivation. Listening to their reasons for applying and what motivates them can be one of the most important factors when making a decision about offering them a position on her team.
The one-hour event closed with a unique question for our speakers about who their childhood superheroes were. It turned out that their superheroes and the values they lived by had a significant impact on our guests’ work philosophies. For example, Iza adored Spiderman and she too now has a dual nature: she is a linguist thriving in the data world. Ali was inspired by Batman and his bravery. Just like him, Ali is pursuing his real passion by working hard and never giving up.
And what would Batman and Superman do if they worked in the data world? “I think Spiderman would be a data analyst,” Iza said. “When he was human, he was a nerd. He was into learning and coding, so I see him on this technical side a little bit. But when he was Spiderman, he transformed himself to be more adventurous and social which is what we need to be when we’re communicating in business. He would do well as a data analyst.”
And Batman would be a DevOps Engineer, according to Ali. “Batman would be doing good because this is who he is. Instead of killing pods, he would give them a chance. Following his MO, in the case of Kubernetes, I wouldn’t kill a pod if it was not working. Maybe I should check the logs to see why a pod is not working and only then, kill it. Eventually, I would kill them but give them a chance as Batman did.”
The only person who can stop you is yourself. You have to believe in yourself and be confident enough that no matter what challenge comes at you, if it’s worth doing, then the hard work will eventually pay off! Patience and good communication are the soft skills you must have to be a good data practitioner. We advise you to start by building a project from something you like and prepare your GitHub account since it will showcase your project when you are looking for a job in the data world. Good luck!