Everyone here is on the same page, and people are always willing to brainstorm and help with things that might be a little outside of their job descriptions, especially if that means we can speed up a project.
Big data developer Mairis Eglitis has only been in the workforce a few years, but his grasp of technology is already impressive. So what drives his ambition? Mairis wants to implement innovative solutions to a technological conundrum: how do you take a big, unwieldy chunk of data and turn it into bite-sized information that makes the jobs of others easier — seamless, even? In other words, solutions that feel simple to others but require much of Mairis.
His appetite for challenge was formed in his childhood when he was diagnosed with Keratoconus, a disease that affects the structure of the cornea and often robs young people of their sight. He credits his mother with shepherding him through the ordeal; she taught him how to persevere in the face of daunting challenges. The treatment was a success, and Mairis was ready to face the challenges the world had in store for him.
Mairis describes himself as having a “teachable personality,” which he brings to bear when explaining new technologies to the people around him, such as clients and colleagues. He says it’s important to communicate effectively and clearly in those situations, making the learning process as pleasant and stress-free as possible.
Read ahead to learn more about Mairis: what stokes his interest in his field, and how big data and Big Timber have a few things in common.
Q. Can you talk a little bit about where you grew up and what kind of upbringing you had?
A. I was born in a small town in Latvia called Alūksne that’s very close to Russia. I grew up with my mom and grandmother. We were never the richest family in town but, somehow, we always managed to get everything we really needed. My mom worked at a local school supply store, selling things like notebooks and pencils, and she’s actually still working there today.
I owe a lot to my upbringing. When I was a student and something didn’t make sense or didn't work out the way I wanted it to, I would get very frustrated. My mom always pushed me to try again, and eventually, I would get past my frustration and find answers.
My family faced a difficult time when I was in seventh grade and started having vision problems. We discovered during my annual vision test that I couldn't see too far away, and it turned out to be Keratoconus. It was possible that I could have gone blind, but my mom wouldn’t hear of it. Instead, she would drive me to different eye doctors – some of them 200 kilometres away. I eventually ended up having two complex surgeries performed to replace cells in both my eyes. So I wouldn't call it a “normal” upbringing, but I would definitely say it helped me build character, learn how to be persistent, and appreciate what I have in life at any given moment.
Q. If you had to describe a data engineer’s job to someone without a tech background, what would you say?
A. I like to use one particular analogy. I ask people to think of big data engineering as a sawmill. You feed raw lumber into a sawmill to make smaller, custom-sized pieces of wood that can be used to create any number of useful things: a chair, a ladder, a roof. Data are really no different. They need to be structured, cleaned, and prepped so I can build tools that provide what people need — something that also provides them with insights.
Q. How did you get interested in this field? Did you plan for it or did it just kind of happen?
It was sort of an accident. I studied computer science at university, but I didn't know what I wanted to do after graduating. One day I was reading about extra courses, ones that might expand my horizons, and I found a class that was all about big data. It caught my interest right away. I ended up doing an internship in the field at my first company, and I stayed there for three years.
Q. The place where you worked before coming to Kaiju was a large IT company. What was that like?
A. I was looking for more flexibility and project ownership than the job provided. The projects at the company changed several times a year, and just as I was getting into a good rhythm, the project would end. That was frustrating. The working hours were also very strict. I had to be available at certain times no matter what, which just wasn't flexible enough for me.
Q. How did you end up at Kaiju?
A. I started exploring freelance opportunities and did some short-term gigs. Shortly thereafter, I was approached by David Schooley, Kaiju’s Chief Technology Officer, and Nicholas Subryan, Director of Artificial Intelligence Systems & Quantitative Research. They wanted to talk to me about a job as a data engineer on the AI team. It was the opportunity I had been waiting for, and here I am today.
Q. What's unique about working for Kaiju as compared to other companies?
A. The biggest difference is the openness of the environment. Everyone here is on the same page, and people are always willing to brainstorm and help with things that might be a little outside of their job descriptions, especially if that means we can speed up a project. I also get along with everyone here on a personal level, and I can talk with them about stuff that isn’t work-related. Honestly, I’ve never been part of something like this before. It’s a great place to work.
Q. Has Kaiju allowed you the flexibility and independence you want?
A. Kaiju has given me total freedom to work the way I want to work. There’s no bureaucracy, no endless levels of managers you have to go through to get approval for every spec. At Kaiju, management trusts their teams enough to leave us to do our jobs in our own ways.
Q. Where do you see Kaiju going in the future?
A. We are working to reinforce the stability of our software, to make the end product function with minimal human interaction. Anything’s possible. The company is growing quickly, so who knows what’s coming in the next decade at Kaiju?
Photo by Ricky Flores
Daniel Bukszpan's reporting and commentary on finance, technology, and politics has been published in Fortune, The Daily Beast, CNBC.com, and other outlets. He lives in Brooklyn, New York.