From Anything to Data Engineering: Episode #1
From Actor to Data Engineer: An Interview with Jeff Vermeire
Communication, problem-solving, and empathy — What Jeff learned on stage made him a rock star data engineer.
Welcome to the DET’s “From Anything to Data Engineering” blog series! At DET, we believe that everyone can build a data engineering career regardless of their background. In this blog series, we interview data engineers from various backgrounds and share their unique career journeys and lessons learned. By telling personal stories, we hope to encourage more curious minds to discover their own strengths and break into data engineering!
About Jeff Vermeire
Jeff Vermeire is currently a Staff Data Engineer. His data career started as a data analyst and before that, he was an actor! Jeff spent 41 years of his life with undiagnosed ADHD and as a result, he has a wide breadth of interests: from tennis, running, cycling, and hockey, to micro-farming, to urban design, to politics, to video games. Most recently, he discovered his passion for camping, after spending a night in a tent with his son in our backyard.
Q: What did you do before data engineering?
Oh gosh. Before I got into data, I was barely surviving. Mostly I was acting and doing lighting design for area theaters, which didn’t pay. I could never decide what I wanted to do with my life, but I was a pretty decent actor, so I thought it was a perfect job for me. What other career gives you the opportunity to be anyone at any given time? I also spent a number of years selling tennis gear, coaching, and delivering pizzas… There are some stories there, but I’ll save that for another day.
On top of all that, I had become somewhat of a professional student: I kept accumulating credits but never graduated. I started in Computer Engineering because that’s what my parents wanted. After taking some time off, I transferred to major in theatre and ended up failing out of school. At one point I tried web design and biomimicry research.
Then I got my first “career” job: a data analyst. I found that I could really dive in and focus for an inhuman amount of time each day. It didn’t really feel like work, it felt like solving puzzles!
That’s the thing that made me fall in love with Data Engineering: that sense of solving complex puzzles that very few others can.
Q: What did you find most challenging when transitioning to data engineer?
Remembering to eat. Haha.
Joke aside. The real toughest thing is companies use various tech stacks and therefore have different requirements for data engineers. I had a solid foundation in data modeling and data pipelines and I know I can learn whatever the new job needs me to. However, it’s very difficult to prove to strangers that I am a fast learner.
Recruiter: “Do you have Snowflake experience?”
Me: “No, but I have extensive experience with BigQuery and Redshift.”
Recruiter: “Well, they’re really looking for someone with Snowflake experience.”
Although this can be frustrating, I believe that as recruiters and hiring managers gain a better understanding of data engineering, things will get better. One approach I use to overcome this in interviews is to be proactive. I’ll often say that “I have equivalent experience with BigQuery and Redshift,” or “I’m confident that I could translate my extensive experience with other tools into picking up Snowflake.”
Sometimes I will still end up with rejection and that’s ok. If the role is dead-focus on a specific tool, that’s not for me. I always want to try new things.
Q: People always talk about transferable skills. Are there skills you learned from acting that helped you become a better data engineer?
First of all, communication! You’re not going to be a successful actor if you can’t engage with the person with which you’re sharing a stage. I also learned how to analyze a document and anticipate what the real “ask” really is, which is never what they say it is. There’s a lot of “reading between the lines” subtext.
My real superpower, though, is problem-solving. During my days as an actor, I learned that whatever was presented in front of me is only an iceberg of the story, and I have to fill in the rest. For example, when I played Lank Hawkins in Crazy for You (which happens to be how I met my wife), I had to put myself in Lank’s shoes to figure out why he was the way he was: “Why was he so resistant to the changes in his community?”, “Where did he grow up?”, etc. I even made the character left-handed to help me get out of the “Jeff” mindset.
In acting, people often talk about the “magic if”:
If I were the character in the situation, what would I do?
It pushes the actor to look through the character’s eyes, not their own. It’s the same thing with data engineering. I constantly try to look at the data through other stakeholders’ eyes:
- If I were a Data Scientist, what would I need?
- If I were a Marketing Data Analyst, what would I want to look at?
- If I were a C-level executive, what would I find important?
Q: What advice would you give to aspiring/new DE?
The best advice that I could give new and aspiring Data Engineers is to be adaptable and study the underlying concepts. The data engineering ecosystem is constantly evolving and whatever tool or technique is hot right now isn’t going to be in 3 years. Whoever can adapt is going to thrive in the industry.
Moreover, if you’re passionate about data, don’t let anyone tell you that you have the wrong background, or that you didn’t go to the right school, or whatever other lame excuses they use to gatekeep you. I currently have no degree and I have been doing this, successfully, for more than 15 years. It wasn’t easy, and plenty of companies passed on me for petty reasons, but I’m here and I’m kicking butt. As cliche, as it sounds, you can too.
Last but not least, anyone that says that AI is going to make data engineering obsolete is delusional. If anything, it’s going to make it even more in demand. How are all these companies going to get all the data to feed their enormous models? Data Engineers. The role is likely going to look different in 3, 5, or 10 years, but that’s always going to be the case in tech.
Thank you for reading! You might also be interested in the following:
- Connecting with Jeff on LinkedIn and Medium!
- Joining the DET Slack community for more learning resources, networking, and mentorship!
See you at the next “From Anything to Data Engineering” episode!
