Meet the Kalibrate team: Conor Williams, Data Automation Engineer
At Kalibrate, we believe our success is driven as much by our people as our technology. Here, we meet Data Automation Engineer, Conor Williams. Read on to find out how an interesting networking opportunity led to him landing a dream position.
What’s your role at Kalibrate?
|I am a Data Automation Engineer, and my primary role is finding ways to automate the data clean-up process, so that as a model is built it gets closer and closer to becoming fully autonomous.|
What does a typical day look like?
Well, we all wake up and go to the bathroom, and from then on everyone’s day is different.
My day consists of checking meetings/emails and since most of the people I communicate with are based in Canada/USA, most of my mornings are free to get the bulk of my work done. If I have free time during the workday, I tend to continue learning via online courses eg Alteryx, SQL, Python — all of which will help me in my day-to-day work.
What do you love about your role?
Work-life balance, flexibility and fun are just a few of the qualities that I love about my role. I get to learn new things every day, whether that be from courses or meetings with people all over the world.
Why did you choose to join Kalibrate?
Bartender to Data Engineer, sounds like the protagonist at the start of a film :), but how exactly did that happen?
Well, as a bartender you get to have these few minute chats with every guest, but the way I saw it, each of those chats was a mini-interview. Fortunately for me I had the pleasure of chatting with Charles Wetzel (CEO of eSite, a Kalibrate business) multiple times over the course of a few months.
One day he found me doing my maths exam behind the bar and was curious as to why I was doing a maths exam (as he thought I was studying hospitality) and then we started to talk about what I wanted to do in the future. He mentioned he had flown over with Justin Tischler (Chief Data & Analytics Officer) and asked if I would be interested in speaking with him and exploring any possibilities of internships/work-experience and of course I said yes. So, Charles told me he would bring Justin down the day after. At that point, all I had was his word…
Come the next day, it was getting close to the end of my shift and much to my surprise Charles and Justin both turned up, which showed me the quality of the leadership at Kalibrate.
If it wasn’t for the transcendent leadership that I had experienced, I would never have researched the company to find that I would love to work there.
After talks with Charles, Justin and Suzanne Beltran (Director of Analytics) who all had a warm, friendly, and polite attitude, I got the pleasure of talking with Jeff Butt over teams who later offered me an internship.
Ever since I have been here, I still get the same warm, friendly, and polite attitude not only from our senior leaders, but from all teams.
What do you think are the greatest challenges and opportunities in the Kalibrate sectors?
I guess there are lots of challenges with location intelligence, primarily being that profitable businesses won’t always investigate location intelligence until they are on a crest of volatility. But when they do, even though they may have been profitable, through the use of the products available at Kalibrate, their business will likely see a large increase in volumes sold beyond what they thought was possible, only through this will they keep location intelligence in mind for other sites.
With location intelligence, it is like going to a casino where the roulette wheel is only red, you know exactly what will happen, but you must go to the casino first.
Where do you see the QSR markets heading?
“History doesn’t repeat itself, but it often rhymes” – Mark Twain. At the end of the day, the fundamental principles of QSRs are still the same but in an ever-growing world of technology, the exponential opportunities of efficiency improving is Brobdingnagian. Whether that be from McDonald’s installing easy to use touch-screen kiosks, to Amazon creating a cashier-less store.
Through this next year I think QSRs are going to be compelled to look at the data and really get to terms with what the data tells them, and once they understand the data, they can then figure out what needs doing to furthermore improve the QSRs with ease.
As technology is ever-changing, all it takes is one piece of new technology to cause a disruption to the existing, and then this whole process will repeat again with ever more complex technology, and the quicker you understand the data, the quicker you can adapt to the change.
Hence, “History doesn’t repeat itself, but it often rhymes” – Mark Twain
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