So Gjok, tell us a little bit about yourself!
I am based in Prishtina, Kosovo, and I have been part of Kin + Carta since October 2023.
I started my career as a data engineer in 2019 when I applied for a data internship in the second year of my university studies in Computer and Electrical Engineering. I was initially more interested in electronics & physics. When I was 16, I used to repair circuit boards to fuel both my interest in electronics, and my savings for university. Considering my passion for technology and the growth potential of this industry, I quickly figured out what I’d like to do in the future.
So how did you end up working in Data?
I moved to data mid-way through my university studies after getting an internship in my second year, as the internship turned out to be fully data-focused. I was introduced to the importance and value of data, as I saw what a big difference it can make to the performance of a company if it’s properly managed.
Tell me about your role. What is it that you do?
Now at Kin + Carta, I work as a Data Engineer for a retail company - together with the team, we’re creating a scalable data platform designed to serve multiple business stakeholders.
What is your typical day like?
I usually wake up at 7am and start my day with a coffee. With my first coffee and cigarette, I read the news to get a general sense of what’s going on in the world. Then, I check my emails and messages and I go through pending code reviews, so I don’t become a blocker to the team and they can progress with their work. I attend the daily stand-ups and check Jira tickets for any updates and pending tasks.
The rest of the day is a mix between coding, and meetings or check-ins with the team, depending on the project pace and needs. Whenever I have some extra time, I try to stay up to date with industry trends, tools, and approaches.
I regularly make use of Python, SQL, Terraform for the infrastructure part, Spark as a framework for big data processing. I also try to track the efficiency of pipelines to lower costs and improve overall speed and quality of data. I end the day with work updates, check-ins, or by reviewing my daily progress.
What’s your favorite part of your day-to-day?
When I get to face challenges I haven’t tackled before. I love visualizing and planning solutions ahead, as well as trying to identify potential issues that might come up within the solution itself. In that sense, I enjoy ‘feeding’ my mind with a problem and challenging myself to come up with a solution before turning to the wider community for ideas. This helps me consider both the bigger picture and the granular details simultaneously, and come up with an all-encompassing solution that excites me to the point of testing it.
Is there one thing you do before a big release on your project?
Before a big release, I make sure to go back and double-check the relevant discussions that have already come up during the software development process. With a fresh set of eyes and with the upcoming release in mind, any scenarios or implicit biases we might’ve missed during the development process may be revealed.
Generally I’m quite a night-owl, as I enjoy the quietness and lack of distractions at night, which allow me to fully focus and deep dive into any work. A cup of coffee, a pair of headphones, and some good background music allow me to tackle any challenges.
What are some of the most important skills to succeed in Data Engineering?
In terms of technical skills, it’s important to have actual software engineering skills. In the pre-big data era, you could rely mainly on SQL to address most, if not all, of your data needs, as most data was centralized in a single database. In today’s big data environment, you have multiple components where compute and storage are decoupled, so it’s important to have a wider understanding of software development and system engineering principles, and how these decentralized elements work and communicate with each other.
Besides the technical skills, problem-solving and communication skills. Understanding the business needs, i.e. what is the data being used for, and creating an optimal data model that allows you to access any relevant metrics in the most efficient way possible. A data model can include 10 tables or 100 tables or any amount, all of which may lead to the same end result, so it’s up to the data engineer to figure out the best approach. In that sense, understanding how the business collects data to build the optimal data model.
What would you advise people who want to get started in Data?
It’s best to start with learning Python and SQL. I personally enjoy Python’s syntax and how straightforward it is. It can be quite slow but in certain cases, it works very fast in larger infrastructures. Python also has a considerable community of users in the data ecosystem and, considering the rise of machine learning and AI, its use cases constantly keep increasing. SQL in data is inevitable, as it has been around for a while and is here to stay.
It’s also good to understand orchestration tools, i.e. how to orchestrate a data pipeline, so the data flows seamlessly through systems.
What do people often get wrong about Data Engineering?
Not to mix the understanding of their role with the financial and biz dev teams’ responsibilities. Data engineers reliably and effectively collect metrics and translate them into a readable format for the business. They use their technical expertise to figure out the most optimal approach for those metrics to be accessible, reliable, and readable for business needs.
How do you like the culture at Kin + Carta? Any special aspects you’d like to call out?
It’s super healthy - my voice is heard and collaborative leadership is the name of the game. I can openly discuss and deep-dive, knowing that ultimately the best approach will prevail. Our team leads are down to earth and communicate with us regularly, and I very much appreciate the transparency. I also have the opportunity to take ownership and extra responsibility, which in turn helps me grow and be acknowledged for my contributions. Since I joined Kin + Carta, I’ve advanced professionally quite a lot, as I get to regularly work with new technologies to build scalable solutions for our clients.
What about the flexibility of our hybrid-first work model?
One of the things I appreciate the most is flexibility and autonomy. I’m personally a night owl. Sometimes I start my day slowly and pick up the pace towards the evening, which works naturally better for me. It allows me to consistently perform better. I also appreciate the regular knowledge-sharing sessions with the wider data teams, as I get to know the cool projects we’re building all around the globe and learn more about the business.
What’s unique about working at a consultancy? Any advice to share for a future employee?
Make full use of the resources and the technology that are available. We work with some of the biggest data partners globally and we can provide for any data needs for any client. Accessing these partners can be difficult in smaller companies and numerous industries. Here we have regular knowledge sharing with the cross-functional teams and we’re offered access to exciting technologies, certifications, and courses to further develop our skills.
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What inspires you in your life and work?
Overall, as someone who enjoys tackling big problems to find elegant solutions, I’m especially inspired by the work of Andrej Karpathy. He’s one of the best AI engineers out there and, among other things, led the Autopilot program at Tesla and co-founded OpenAI. One notable quote from him is that “you need to feed yourself with the problem before the solution presents itself.” So from him, I’ve learned the importance of deeply understanding the root cause of any issue before starting to design solutions.
As a fun hobby, I enjoy playing Call of Duty Mobile - I was ranked as one of the top five across EurAsia!
