Transitioning to a Career in Data Engineering
A podcast episode I did with Justyn Makarewycz from Baruch College
👋 Hey, this is David. Welcome to the next edition of the Data Engineering With David newsletter. The plan for Data Engineering With David is to create the resource I wish I had when I was in grad school learning to be a Data Engineer.
Today’s article is a transcript of a podcast episode I did with Justyn Makarewycz.
Justyn is the Associate Director of Employer Relations at the Graduate Career Management Center of the Zicklin School of Business at Baruch College, where I did my master’s degree.
The episode covers:
1. My career transition from teacher to Data Engineer
2. How to get the most out of your education as a student
3. Building top-notch Data Engineering projects for your resume
4. Common Data Engineering interview questions
5. How to find role models to guide you in changing careers
Listen to the episode:
You can also listen on Apple Podcasts here.
I hope you enjoy the episode. Let me know what you think in the comments!
0:00:00 - Justyn Makarewycz
Welcome listeners.
I'm Justyn Makarewycz, Associate Director of Employer Relations at the Graduate Career Management Center of the Zicklin School of Business at Baruch College. Thanks for tuning into this episode.
Thank you very much for tuning in to the GCMC podcast. In this episode we're very excited to talk about our MS Information Systems Data Science Concentration alum, David Freitag. David, thanks so much for making the time for being here and talking with students now that you're an alum.
0:00:34 - David Freitag
Yeah, Justyn, thanks for having me.
0:00:35 - Justyn Makarewycz
Before we dive into this article that you had posted and this content channel and LinkedIn, I would love for you to introduce yourself from your background really quickly for listeners.
0:00:48 - David Freitag
I'm David Freitag and, like Justyn said, I went to Baruch and I graduated in the spring of 2021, and I did the MSIS with a concentration in Data Analytics, and I am currently a Data Engineer at a company called American Family Insurance. But my story is that I used to be a high school English teacher and I did that for six years. I am from Wisconsin originally. I grew up in Wisconsin, I went to college in Wisconsin, I taught high school English for six years there, and then I moved to New York. I spent a couple of years working at a tech startup, and then I wanted to pivot my career. So I went to Baruch for grad school, and that was the ticket that taught me what I needed to learn and help me change my career path.
0:01:35 - Justyn Makarewycz
Now, why did you decide you wanted to change that career path from teaching into doing Data Engineering or data data-driven decision-making, whatever it might be?
0:01:44 - David Freitag
So I started out as a teacher and there are parts of teaching that I really loved, and maybe we'll even talk more on the podcast about teaching related things I'm doing now. But if you have any friends, if anybody listening to this has any friends who are teachers, teaching can be a stressful career and, depending where you teach, the pay can be not so great. And so I was thinking, as I was having my quarter-life crisis, I was like: I want to try something different. I started looking for other jobs and I got hired to work at a tech startup in New York City, and that was how I ended up in New York.
When I worked at this tech startup, I was basically paid to teach the clients. So people would purchase this digital marketing software and then I would teach them how to use it, teach them how to run marketing campaigns and things like that. I really liked that job because it felt like a natural progression out of teaching and I wanted to get my foot in the tech world. And then COVID hit and the company is a startup and so, like, half of our clients quit in the same month and the company started to go out of business. And we thought it was--everybody was like--oh my God, it's the next great recession, right? And they were like, look, we don't need you to teach people. We need you to sell. We need you to become a salesperson and get us new business. And sales is definitely not my thing.
And I thought, all right, I've been thinking about my next career move. Now might be the time to make a switch. So I had a friend at the company who was a Data Scientist and I thought, oh my God, I love Peter's job. It sounds so cool, I wanna do that. And I talked to him. I talked to a bunch of other people who were data scientists and they had all gone to graduate school and I was like: okay, this is what I need to do. I need to figure out how to get myself into a graduate program. I need to learn all kinds of things and that's it. That's what I have to do. And so I looked for graduate programs in New York City and Baruch is at the top of my list because it was very affordable.
I went to the University of Wisconsin for undergrad and you get in-state tuition, and I graduated with no student debt, which was... I know it's like amazing in this day and age and I was really lucky. I got a bunch of scholarships and I had good jobs and things like that. But I was like, all right, I want to do the same thing for my graduate degree. I want go in-state, so to speak, and I know the City University of New York is... that's what it is for New York City. Everything was online because of COVID and I was like, okay, I can get in-state tuition, I can do this whole degree from my bedroom, and I could be in and out in like two semesters. And that's what I did for my degree. I did two semesters and it was a really intense period of my life where I was just drinking from the fire hose of knowledge every day, but in like a year I transformed my career and my life looked very different as soon as I got out of the program. It was like I accomplished the goal that I set out to do and Baruch was, of course, very important in helping make that happen.
0:05:08 - Justyn Makarewycz
So impressive, Wow. I mean you made that happen for yourself, David. Obviously, Baruch was just sort of there as an opportunity, but wow, just to hear that experience, that background, I'd never even thought of the way that you put together the teaching part and how those skills ended up bringing you into sort of this kind of universal, not only in the role you had at the tech firm. But you know, I'm kind of seeing now this whole tie of teaching and your new content channel in fact, and I would love to hear a little bit about why you decided to start that new content channel around Data Engineering and these roles.
0:05:49 - David Freitag
Yeah, so I was a teacher. I did that. I know what that's like, but I don't want to be teacher anymore. Not for my career, my main career, I want to be a Data Engineer and I really love being a Data Engineer. But there's still part of me that has the teaching bug, like I really still enjoy teaching, there's a reason I went into that.
Something I've been doing on the side for about the last year or so is I've been tutoring online and I tutor Data Science and Data Engineering, and it's mostly like... most of my tutoring students are graduate students and they're doing... they're basically people who... I have a profile on a tutoring website, and they are doing master's programs very similar to like the one that I did at Baruch. They're looking for somebody who's a couple years ahead of them and who has industry experience, who can help them get through the program, and so that's been my side gig: doing this tutoring on the side and basically teaching people what I learned in graduate school.
And a quick, shameless plug if you're listening to this and you're interested in having me as a tutor... If you're a Baruch student, send me a message on LinkedIn and I'll give you a discount if you want to sign up for tutoring with me!
But anyway, so I've been doing this and it's been fun. It's been like a nice little side gig and I was like, you know, it would be great. I'm only tutoring one person at a time. What if I taught a class to lots of people? You know, I used to teach like 200 high school kids a day. I think I can handle teaching Data Engineering stuff online to adults and people who are already in the industry, or trying to change careers or something like that. But if I want people to be willing to sign up for a class with me or to pay to take a class with me, they have to know I exist, they have to trust me as a teacher. I have to have credibility and so I'm creating a lot of writing. Most of it's on LinkedIn or connected to LinkedIn, and then I've been putting things out on YouTube. So I'm teaching what I know and my goal is to become... I want people to be like okay, David is this source of knowledge for Data Engineering stuff. Right? He has credibility. People can see: what is it like? What would it be like if I took a class with David? Well, I can watch a YouTube video and see.
And my goal is: I want to run a class of my own and I'm not even sure exactly what that would be yet. And there are other people out there in the software engineering, Data Science, Data Engineering world who are doing basically this. There's a guy named Zach Wilson who runs like a class for mid career Data Engineers. And so I look at other people doing this. I'm like, wow, wouldn't it be great? You know, I could combine this... like I really love my current career path, and I have this passion for teaching. It feels like this great mix of all these things that I that I really like to do and that I think I'm relatively good at. And so that's the vision, that's what I want to try to do.
0:08:49 - Justyn Makarewycz
That's great. So let's go through your article Again. The article is... and we'll obviously have a link to it in the description of this episode, but the article called The Entry-Level Data Engineer Roadmap. So what spurred that? Take us through your idea about putting that together, because it's incredibly dense, it's it's super structured and it really is a roadmap. I'd love to hear about that journey and that process.
0:09:15 - David Freitag
I have like a LinkedIn profile and I put on there... I have some info about me, and people who are changing careers, particularly if they're coming from teaching, will will reach out to me and they'll say like, "Hey, can I do like a 20 minute coffee chat with you? I just want to pick your brain." They asked me about my career path and things I learned, and some of the stuff we're talking about today. People I talk to who want to become Data Engineers, sometimes they're data analysts. Sometimes there's somebody you know doing something else entirely and they're like, "I don't even know where to start." Maybe they're not totally ready to jump into graduate school or they're just looking for, "Can somebody show me a map? I really want to know what would this look like if I were to try to do this."
Multiple people have asked me that question and I've had that conversation with people. So I took my notes from other times I've had this discussion, like here's what you should learn, your step one, your step two. I put it into an article with a set of resources and it has links which are, in my opinion, the best places to learn all of these kind of different skills. A lot of this, by the way, are things that I learned at Baruch. I've structured this as almost like a start to finish syllabus, and I know the courses at Baruch are more thematic. But all this stuff... it's things you could learn on the internet, but it's also things that you would learn in an MSIS graduate program.
0:10:53 - Justyn Makarewycz
Right, and it really plugs from a technical perspective what students can do to really beef up their technical skills. One really great section which I'd love to hone in on is about students creating their own projects. So if we go to that section, because it's really entrepreneurial, can you walk through what it was like for you to create your first project? Like how did you get this idea and in your mind that, "You know what, David, you have to create a project for yourself that you can put that on your resume and talk and hopefully have an opportunity to talk about it?"
0:11:31 - David Freitag
Yeah, so I'll say two things. One is that I did a project through the data warehousing class. I'm not sure if that's still the title of it, but when I took it, I took a data warehousing class at Baruch and the professor for that class had us do a project that was like... we worked on it all semester and that project became the project that I talked about in my interviews when I was applying for Data Engineering jobs. I came up with my idea for that project as part of that class and I think I even linked it in the article. It was basically like... it's just... in Data Engineering it's called an ETL pipeline.
That's basically moving data from point A to point B, and point B is is an analytic data warehouse that you can then connect out to other things, like a Tableau BI dashboard, and basically, you know you want to be able to show that you can set all this up because you can then talk about it to an employer. And so I think that's there's this project I did when I was at Baruch and that was hugely useful for when I was applying to jobs. For that project my current boss told me, he's like "Oh, you did that? Well, that's basically what we do every day here, so I know you can do the job." So there's that project. But I would also say I have since done other projects just for fun on my own.
And if you pick a project topic, if you pick something that you're intrinsically interested in, you will fall down the rabbit hole and you learn so much and this is like.. I'm not the only person who's going to say this, or lots of people who say this.. if you pick something you're interested in, you will just kind of naturally learn all kinds of information that will help you accomplish whatever this goal for the project that you're trying to build out is.
And so, I have other projects on my GitHub. I did this one project, which was basically.. I built a streaming data pipeline, it's kind of like creating a carbon copy of Reddit, the online forum website. I was streaming comments and posts from that, and that was so fascinating to me. I learned a ton of things that I would never have otherwise touched in my day job, and so I would say, to anybody who's looking to to learn: find some project you're really interested in. That is what's going to cause you to be incredibly motivated and go above and beyond to learn things on your own that maybe you wouldn't even learn in your classes, that you wouldn't even do in a regular job. That will really level up your skills.
0:14:07 - Justyn Makarewycz
That's great and, David, when you talked about your projects, like in interviews, do you remember what the interviewers wanted to hear and what they really wanted to take away from your describing the work you did on them?
0:14:21 - David Freitag
Yeah. So I think there's a couple things that hiring managers are looking for. There's a baseline level. They're like, "Okay, does this person have a foundation of technical skills? Were they able to learn enough in their graduate program or whatever it is that I know they can do the job? So you have to be able to, when you do a project on your portfolio... hiring managers don't have time to like look at it, they want you to talk about it in the interview. And you have to be able to talk about it in enough technical detail. And they'll say, "Tell me all the technical details. Don't hold back. I want to hear it all." One piece is, "Okay, can this person really do the job?" That seems obvious.
The second piece, which is maybe not so obvious, is something that hiring managers are looking for is: did you encounter problems, and challenges along the way? And if you did, how did you deal with addressing those? How did you solve those challenges? How did you teach yourself? How did you utilize resources around you? How did you look for more information? And they want to see: are you resourceful? Because, especially in a role like being a Data Engineer, a lot of what I do, not only have I never done it, but nobody on my team has ever done it before. It's like bleeding-edge new, which is super interesting, but it also means like going to run into problems. Be resourceful, do you know how to solve problems that you've never seen before? That nobody else around you has ever seen? They want to know: can you be resourceful? Can you think? Are you motivated to chase down solutions? And that's important to communicate through how you talk about your project.
0:15:58 - Justyn Makarewycz
And sometimes it's interesting candidates... actually they're fearful about talking about problems that they've encountered instead of actually embracing the fact that people want to hear about them and get a sense of how you overcame them... whatever you did to then fix any bugs or issues. And it's interesting how sometimes it can't just be always a perfect story. The problems are actually the gold.
0:16:24 - David Freitag
Absolutely. And it's like you know, in any kind of job, you are going to have problems. You are going to run into issues. It's not about how many times you succeed, it's about it's about failing and learning from failure. It sounds like a lot of cliche advice, but this is what it means specifically. It means you encountered a challenge. You did not solve it. You tried to work through it, even if you didn't figure out the solution. Like, are you resourceful enough, are you kind of like, aggressive enough at problem solving to attack it and not just throw your hands up and say, well, I don't know? That's something that hiring managers are looking for in somebody they want on their team.
0:17:02 - Justyn Makarewycz
Totally. You mentioned also a couple of things about Baruch and how it impacted you, which is really great. If you're looking back at David in, I think it was probably when you graduated in 2021... but you started your degree in 2020. Is that right?
0:17:19 - David Freitag
Yeah, I started September 2020. I graduated in May 2021.
0:17:24 - Justyn Makarewycz
Okay, so looking back on David in September 2020, on what you've learned starting your degree, graduating, etc., what do you wish you had known back then when you were a student that you know now?
0:17:41 - David Freitag
Yeah, this is a really great question that I know you sent me before we started talking. I really kind of struggled to come up with exactly what to say. There are a lot of things that I was lucky, I think, to learn along the way. These are just like different technical things or things that I just learned about navigating, like what's the difference between a Data Scientist and a Data Engineer?
I went to graduate school and I was like, oh, I want to be a Data Scientist. I had never even heard of Data Engineering until I was in my graduate classes and learning some of those skills. So some of it was things that I just I had learned, I think, just naturally, through being in an environment where you're surrounded by other people on a degree journey. If there's something that I wish I had done more of, you know that I didn't do and that I would tell somebody to do, and don't make this mistake I made... I wish I had found more role models going into this. So, for example, like I talked to a couple of Data Scientists before I went to graduate school, but I got my first Data Engineering job and I had never even talked to any Data Engineers!
Before I did this... it seems ridiculous to say that out loud now... I had taken classes in those skills. I read job descriptions, I had done projects. So I felt like I knew what I was getting into. But I really wish I had done more reconnaissance and talked to some more people, or tried to find people. I did some of this eventually, like find people who were a couple of years ahead of me, who went to Baruch, you know I did that kind of thing.
I met some of those people through GBAP, people who were GBAP alums. That was like a good resource for me, but I wish I had done more of it. So now, I am trying to be a relatively publicly visible role model for other people who want to be a Data Engineer. Like well, what does it look like? David's done it, I guess. I can take a look at him.
0:19:37 - Justyn Makarewycz
So what's next? What do you foresee kind of a next piece of content that you're probably going to be working on or have already maybe started or thinking about?
0:19:48 - David Freitag
I think like my plan right now is: I'm building out a SQL tutorial series. So I'm like halfway through the intermediate SQL one... It's a checklist of the things that you should know if you're going to write SQL in any kind of job, even a Data Analyst job. Part of it is I want to make sure I get good at creating YouTube videos, and I need to kind of step back into the role of like being a teacher. There are tons of SQL tutorials out there, so I'm not expecting lots of people to go, "You know David's tutorial is so great!" But I want to start somewhere.
There's another guy named Alex Freberg, who is a Data Analyst. You can find him on LinkedIn and he has a really big YouTube channel. But he basically built... if you want to become a Data Analyst, you can watch his YouTube channel. He has hundreds of hours of YouTube videos and it's kind of this comprehensive program on how to become a Data Analyst. There's something about the idea of putting my knowledge out there just in general that really appeals to me. So I want to finish this SQL tutorial. A part of me is like, "Oh, maybe I want to build the rest of... what does it take to be a Data Engineer?" And I think that the thing that is going to direct my attention most is like... people reach out to me on LinkedIn and they ask me questions, and if people are asking me questions about stuff, that's probably what they want to know. That's probably what I should do. I know that's kind of a non-answer I just gave you.
0:21:22 - Justyn Makarewycz
But it totally is. I mean, I think it's kind of great that you have a little bit of... some market intelligence of people reaching out to you with these questions that spur ideas. I mean, that makes a lot of sense. David, what was the whole job search process for you after graduation, or even during graduation? What did that look like for you?
0:21:44 - David Freitag
Yeah, so I applied to a bunch of jobs. You know, the way everybody does. I applied to lots of things on LinkedIn. I tried to find things on other job aggregators. I also applied to jobs through... there's like a... I can't remember exactly the name for it, but I think the GCMC at Baruch has a job website and there are a number of companies that Baruch has really good relationships with. I worked at Pitney Bowes for an internship during my degree and I know Baruch has a great relationship with Pitney Bowes, so I applied.
I only got two interviews. One of them was a job that I applied to through the GCMC website, and then the other one was my current job where I got hired, and I got that one through a referral. I know somebody who works at the company and I applied and got a referral. So I'll say here, leveraging your network right is the common advice, and in my scenario... it's like, "Well, I have a referral and I have the GCMC, that's my network." And that's what led to interviews for me. If that hadn't worked out, I would have probably had to just continue applying to lots and lots and lots of other positions. But I think I got relatively lucky in that I got some quick wins. I think it was in the summer, like soon after I graduated, I was interviewing and I started my current job, I think in August.
0:23:06 - Justyn Makarewycz
Oh, wow, okay, so that was that. That sounds like it was quick. In your interviews that you've had for roles, were there common questions that were being always asked to you?
0:23:16 - David Freitag
For Data Engineers specifically, there's definitely a SQL technical interview round where they ask you common SQL questions. The one that everybody always asks is, "What's the difference between the WHERE clause and the HAVING clause?" And so if you're going to be having Data Engineering interviews, you should look that up. You should know the answer. But basically, like for Data Engineering, you need a base. You need a base skill set in SQL, for sure, and then of course, also in... they want you to have some Python knowledge. But SQL is really the bread and butter. And then cloud technologies, and it doesn't matter as much which cloud platform, but just that you understand how to do things at scale using cloud resources. If you know one, you can learn the others. But they want to know that you understand how the cloud is different than an on-premise system.
0:24:13 - Justyn Makarewycz
Well, congrats on that entire process. That's, fantastic, David. What have we not talked about that you think is important still to mention?
0:24:22 - David Freitag
Oh my gosh, I wish I had thought of that. I don't know if I have any other exciting tidbits of wisdom to share, but I would just say I did have a really great experience at Baruch and it was hugely pivotal in helping me shift my career.
And I think if I had to give blanket advice to anybody who is currently in college or graduate school: take this time that you're in school and think of it as this, like very special time in your life. You're kind of like a butterfly, or you're a caterpillar, you're going into the cocoon and you're just like... I took as much out of Baruch as I possibly could. It was my number one priority for an entire year. I think that some of the success that I've had has been because I really took my learning seriously, and I took everything I could out of Baruch. Everything that I could find, I leveraged it. I didn't waste that time, I didn't waste those people. I feel that was the right choice, and it paid off for me. So that's the advice I would give to somebody else.
0:25:30 - Justyn Makarewycz
Fantastic advice, love it. Thank you also for the shout out to the GCMC. Truly appreciate that. GBAP, I think they're going to be really excited actually that they've got an alum who's who got a lot of your experience with the club. So, Dvid, truly appreciate the conversation and we hope to have you back on campus soon, or potentially even on another episode down the line too, depending on on what you're doing. I think it's going to be a lot of great stuff coming from you.
0:26:00 - David Freitag
Yeah, thank you so much, Justyn. I really appreciate the opportunity.
0:26:08 - Justyn Makarewycz
Thanks, listeners, for tuning into the GCMC podcast, where we look to get off the record thoughts and perspectives from individuals who have been hiring managers and in hiring positions in their careers. The GCMC is here for Zicklin MBA and MS students and alumni for their careers wherever they are, so be sure to stay in touch with us.
This episode was transcribed with the help of Podium: https://podium.page