Ever wondered what it’s like to work at Silectis? We’re spotlighting our employees to give you a peek into our lives in and outside of work. For our first spotlight, we hear from Brendan Freehart, a true Silectis veteran who’s been with the company for almost 3 years.
Brendan is a Data Engineer at Silectis, meaning he partners with our clients to help them get productive with Magpie, our data engineering platform, faster. He’ll explain more about what this work looks like below.
Get to Know Brendan
What do you do at Silectis? Where were you before joining the team?
I’m a data engineer. I go into our client engagements and help them get productive with Magpie, sometimes setting up some of the data infrastructure that Magpie uses to bridge the data engineering skills gap. Before Silectis, I was working at an IoT company doing more of a data science/data engineering hybrid role. I would do more machine learning and analytics type stuff.
What’s your favorite part of your job?
My favorite part of being a data engineer at Silectis is the ability to work with a diverse, everchanging set of client needs, data types, and goals. I get a full range of use cases for data engineering. When you get into real life use cases for data engineering, there’s a lot of wild stuff that businesses need to get done. I really like being a data engineer at Silectis because I’m not locked into one business model, use case, or approach to using data. I can look at telemetry data, ERP data, and all sorts of other stuff. As a data engineer, it keeps you on your toes to constantly be working in different contexts.
What’s one thing you’ve learned since joining the team?
How the proverbial sausage gets made when going from a very new startup to an expanding, growth-oriented company. Seeing the fight that has to go into getting a small company with a great idea to be successful has been really unique.
What advice would you give someone looking to get into data engineering?
My advice falls into two buckets. The first is skills-based. Being comfortable and flexible and versatile with cloud infrastructures (AWS, Azure, GCP) and being able to work within their data toolkit, or even more broadly with tools like Apache Spark. Being adaptable and being able to work within these frameworks is helpful and makes you more self-sufficient as a data engineer. Additionally, data modeling is something you want to be comfortable with, even if it’s just the fundamentals. You’ll need to know and understand how data warehouses work. Most companies that you work at will use some data modeling techniques – the end goal is to make the downstream consumer as productive as possible.
Second, more general career advice. Network as much as you can. I was pretty allergic to networking early in my career as I found it transactional. Now, I’ve learned that it doesn’t have to be that way. Talking to folks with jobs that you’re interested in can really help you learn and understand career trajectories, how to get a start, trends, and more. Talking to other people will help inform your own mental model of the industry – almost like someone checking your homework. (Editor’s Note: If you’re an aspiring Data Engineer who’d like to connect, you can find Brendan on Linkedin here.)
How would you describe Silectis in 3 words?
Better data engineering
How do you spend your time outside of work?
I spend a lot of time in activism and volunteering for various community organizing groups.
What’s one quarantine hobby or activity you’ve picked up?
I’ve started playing the fiddle.
What will your next tattoo be?
A woodpecker! Just got it last weekend. You can see it on my left arm above.