Meet The Team: Evan Volgas, Data Engineer

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Evan

These products can’t just make themselves.

Countless hours (and coffees!) get spent tweaking every aspect of our platform – from making sure our data is up to date, to adding new and valuable features. This is all to make sure our users get the absolute most out of WhatRunsWhere. Lucky for us, our Development Team is always up to the task!

This month we unplugged and talked with our Data Engineer: say hi to Evan Volgas…

1. First things first, tell us a bit about what you do at WRW?

I work on the dev ops team at WRW and specifically I’m responsible for managing the data pipelines and keeping them operational. We’re also working on some improvements in our data infrastructure, and I’ve been hard at work on those.

2. What is your favourite part about working here?

Well, one thing I definitely like about working with WRW is, at least on the data side, we’re solving some problems that don’t have any sort of textbook solution. I think there’s a difference between software development and software engineering, and we’ve got quite a few challenges here that involve much more engineering than they do just development. It makes it a lot of fun.

On the one hand, it can be pretty overwhelming sometimes. But on the other, you definitely stay challenged and have lots of interesting problems to work on. That’s a plus, especially for people like me who get bored easily.

3. When you’re not in the office, what are some of your favorite things to do?

I read a lot. I also have two very special dogs named Karma and Kazi. They’re kind of like my kids in a lot of ways and I spend as much time as I can hanging out with them. I also tap dance (no I’m not kidding) and cook lots of vegan food.

4. Name a couple things that top your bucket list?

Live in Brazil. Visit Ahmedabad and Porbandar. Rent a motorcycle with a side buggy, those old WW2 kind with the really loud engines that stutter all the time as if they might spontaneously just stop working. Karma is an English Shepherd mix who loves cold weather and the wind so she’ll be the perfect companion on this road trip. I have no idea how to do it and it couldn’t be done safely either, for that matter. But for years I’ve had this mental image of driving across an abandoned highway with Karma in the side buggy and a pair of goggles. At least as I imagine it, she’s got her tongue out and is smiling the whole way.

5. Who is your mentor and why?

My mentor… probably a guy by the name of Andre’ Stephens. He was my first boss at a little nonprofit in the middle of nowhere Arkansas. He left a successful investment banking career to start his nonprofit and just generally has a lot of really interesting views on how to make decisions in the face of uncertainty.

Math/data people like me aren’t necessarily keen on not knowing things. For that matter, we’re not always very comfortable when we don’t have all the info that we want to have, all the data. Andre’ really taught me a lot about how to make decisions when you aren’t totally sure, and what sort of questions you need to ask yourself before you do that. I really learned a lot from him.

6. What’s your best advice for those looking to pursue a successful career in Data Engineering?

This will probably sound like I’m contradicting what I said about learning to make decisions with uncertainty,  but the best advice I can give anyone going into data engineering (or anything data related at all for that matter) is that accuracy is king.

Everybody always wants answers right now. You will be pressured at some point to deliver results faster than you actually should. But delivering results you haven’t checked carefully doesn’t really fly in a data field. The thing to keep in mind is, unlike when you were in school, 90% correct isn’t an A where data is concerned; it’s a disaster.

If you’re wanting to go into a data field, learn to poke holes in your results, how to prove them wrong or right, and how to explain your tests to others so they too can be confident in them. Whether you’re a data analyst, engineer, scientist, or just someone who uses data a lot, the ability to prove a result right or wrong is very valuable. And it’s the kind of thing you should start practicing as often as you can.

7. If you weren’t a Data Engineer, you would be a full-time __________________________.

If I weren’t a data engineer, I’d either be a professional tap dancer or I’d be an applied mathematician. I used to dance professionally, and at one point was studying for a PhD in computational science! I got out of the former due to an injury and the latter because I was too old when I went back to school to really get into it anymore. I still do love math and tap dance, though, and try to keep both skills as sharp as possible. So if I didn’t do data engineering, it’d probably be  because I stuck with either math or dance.

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