In this bonus episode, Eric and Kostas preview their upcoming conversation with Kevin Liu of Stripe.
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Eric Dodds 00:05
Welcome to The Data Stack Show PRQL. This is a short bonus episode where we preview the upcoming show, you’ll get to meet our guests and hear about the topics we’re going to cover. If they’re interesting to you, you can catch the full length show when it drops on Wednesday. We are here on The Data Stack Show with Kevin Liu. Kevin, thank you so much for giving us a little bit of your time today.
Kevin Liu 00:28
Yeah, thanks for having me.
Eric Dodds 00:30
All right. Well, you’ve done a couple of really interesting things in data. But just give us your brief background. How did you start? And what are you doing today?
Kevin Liu 00:38
Sure. I’m currently a software engineer at stripe, I’ve been working there for around three years, been working with data infrastructure there. So a lot of open source technologies, such as Trino Iceberg, my team powers, our internal BI analytics. And recently, I’ve taken on another challenge with on the data product side, the product is called stripe data pipeline, we essentially enable merchants to have their stripe data back into their warehouse into their data ecosystem. efficient way.
Kostas Pardalis 01:20
This is great. So actually, I know you’ve given for a while now we’ve been talking like, since like the times where I was the time when I was like at Starburst, and about Trino specifically. And I’m very excited today because I mean, I had like the, like, let’s say the opportunity and the pleasure like to work with stripe quite a few times. And it’s one of these companies that they’ve been around for, like long enough to, you know, like go through like many changes, but always like trying to stay up at the forefront of what is happening out there. For example, like very early adopter of Spark, right? I’m pretty sure you probably still have pipelines in Skyline where because of that. And you keep innovating. We are open like using like new technologies. And many things have happened in these like past 10 years, let’s say. So having you from there, and you being like enough, long enough, they’re like to see these past like, three, four years, like the evolution, I think will give us like a great opportunity to talk about what data infrastructures today. what others say some interesting problems are. And also based on what’s like your latest, like moving to like turning data into products. Talk about that, because I think it’s like a very important next evolution state when it comes to like to infrastructure around around data. Right. So what I’m really excited about today, well about you like what are like few things that you’d love like to talk about?
Kevin Liu 02:56
Yeah, I think, in general, I’ve been really happy working at stripe just because, you know, the company for its sides for the kind of engineering culture there. It really helped me learn and get to understand a lot of what is going on, especially in the data world, kind of at the like, you know, what is the most newest and shiniest thing that we can work with? Right? So, you know, I took a database class in college, didn’t think much of it into stripe, started working with, you know, OLAP systems Trino Iceberg, and it was very new to me. But then eventually, I started to realize that it was new, kind of to the industry as well. And that’s been really exciting to me in order to say okay, well, you know, how do I take this new concept? How do I run it efficiently as stripe? And then how do I help the community? Because it is an open source project? How do I kind of take ideas that we have that we come up with, and share it with the community as well. And then on the data product side, I think Stripe is positioned very well to do you know, data sharing. Not a lot of companies can do that, because not a lot of companies have, you know, the value from the data that they have, and have that kind of be shared to their customers in a way where the customers are asking for on a daily basis. So you know, I’m still learning. I think I just want to share some ideas with you guys. And yeah, happy to talk more about things.
Kostas Pardalis 04:48
Yeah, let’s do it. What do you think, Eric? Are we ready?
Eric Dodds 04:51
I was born ready. cosas I was born ready.
Kostas Pardalis 04:54
I know that. Let’s do it. Let’s do it.
Eric Dodds 04:58
All right. That’s a wrap for the PRQL. The full length episode will drop Wednesday morning subscribe now so you don’t miss it.
Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
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