Advancing Her Technical Prowess: Meet Dartmouth MEng Student Emily Marciniak

When Emily Marciniak, a senior data engineer at Disney, first began working in data almost a decade ago, she couldn’t have foreseen the turns her career would take. After earning her bachelor’s degree in business and IT, she graduated into a world fascinated by data and its potential insights. “A lot of opportunity put itself in my way,” she recalled of the timing. 

Marciniak began working as a data analyst, but over time, emerging spaces like cloud development combined with her love of problem-solving led her to data engineering. As a new data engineer, Marciniak had opportunities to learn on the job and take courses to further her technical prowess, but she knew a master’s degree would likely be a smart investment for longer-term growth, providing the solid technical foundation she wanted and exposing her to ideas that could possibly shift the trajectory of her career. 

Dartmouth’s online Master of Engineering in Computer Engineering, offered through Coursera, stood out for several reasons, including the program’s technical coursework and flexible scheduling, as well as Dartmouth’s storied history with AI. “I really believe this program is a very high-impact graduate degree with a lot of flexibility,” she said. 

Marciniak spoke with Coursera about her decision to enroll at Dartmouth, the global connections she’s made with her peers, and what the MEng program has been like. 

Tell us a bit about your career so far. What have you been doing? 

Emily Marciniak: I'm about a decade into my career and I've spent most of it in data. I started off in the analyst space, then I got into cloud development, but my career has gotten a lot more technical as I've gone on. Now, I'm working for Disney as a senior data engineer. 

Why did engineering feel like a good fit?

Marciniak: I've always enjoyed troubleshooting and problem-solving, and that’s a large part of what I do on a daily basis. I love coming to a solution and advancing whatever the idea is. 

STEM tends to be such a male-dominated field. How have you navigated that space?

Marciniak: Doubt can really create a negative mindset and limit your reach by creating unnecessary barriers. Personal confidence has been crucial in helping me navigate this space. When you become strong in what you do, that will naturally build confidence. 

Part of this journey has also included a lot of self-reflection. I’ve had to teach myself not to worry so much: whether that be asking the wrong question or making mistakes. It's been a process to overcome—and trust me I still have moments—but shifting my priorities to what I need to achieve rather than giving focus to things that are out of my control has made my day-to-day much more freeing.

When did you start thinking about earning a master’s degree? 

Marciniak: About five years ago. I was working with Anheuser-Busch—that was my first transition into cloud development and a higher technical level. I was able to learn a lot on the job, but from that time on, I really wanted to have a foundation that would allow me to excel in any direction.

What stood out about Dartmouth’s Master of Engineering in Computer Engineering?

Marciniak: I wanted a deeper technical understanding so I could be the best technical resource in my role. But I also wanted to prepare myself for whatever was next in my career. This program came out on top for me. The coursework is really well-rounded. I was also looking to maintain my current career while going to school. Dartmouth’s program being online fit into my schedule really well.

What was it like going back to school?

Marciniak: There was a bit of a learning curve. But a lot of the other students are also working at the same time. The professors have been really understanding. They've made the experience what it is for me. Our course sizes are also really manageable. We don't have hundreds of students in them. That's really nice because it means my professors know my name. When I email them, they know who I am.

Learn more: 13 Tips for Working Full-Time and Going Back to School

What has the coursework been like? 

Marciniak: My first course was machine learning and it was Python-based, which was great because I had a background in that programming language. It was a great transition into this program because it basically extended skills that I knew, but implemented them with an entirely new knowledge base.

What’s the routine you’ve structured to balance work and school?

Marciniak: I’ve been really intentional about my time. Going into this program, I knew some of my free time would get allocated to schoolwork. The first thing is fitting in the coursework itself. Then, I try to understand what sort of discussion topics I have, or if there’s any teamwork due. I find if I do a couple of hours every night that works better than just studying for several hours a few nights a week.

Have you gotten a chance to connect with any of your peers?

Marciniak: One of the coolest opportunities with this program has been networking through team projects. My team right now, there are two of us on the east coast and then there's one in Tokyo. It’s really cool getting to learn from everyone.

Have you been able to apply anything you’ve learned right away to your work?

Marciniak: Yeah, actually! I’m currently taking Embedded Systems and we are programming in the language C. We are using a compiler. It helped me better understand what my team is doing in my current role from a procedural standpoint: why we do certain things in certain orders or what might be a more efficient way of working within our command line. 

How great that you don't have to wait to graduate to begin implementing what you’ve learned! 

Marciniak: I think that's one of the best parts about this program. Most of the students in it are working full-time, so you come to the table with a lot more experience and things to talk about. A lot of the stuff we're doing right now is either applicable directly to what we're working on or you can think about it in those terms.

Do you have any advice for women interested in pursuing a career in STEM or data engineering? 

Marciniak: When you're just starting out, you have a golden opportunity to learn because there's less pressure to have answers. Ask questions often and to many people. Get an understanding of what your strengths are. Then, find what interests you and what is in demand for your discipline and learn as much as you possibly can about that area. 

You are a work in progress. As a data engineer, I often think about how we structure our pipelines in a CI/CD (continuous integration and continuous delivery) deployment—basically, iterating to incrementally make it better. Use every day to get a little better, learn something new, and hone your skills. It won't happen overnight, but I've found the smallest changes can lead to significant improvements over time. 

Lastly, what do you hope to do with your MEng?

Marciniak: I want this to take me to the next step in my career. One of the things that excited me about this program was that the term ‘AI’ was actually coined at Dartmouth. They had a summer workshop [in 1956] and a paper came out with AI as one of the concepts. 

Now AI is a new frontier. To be in a program that has an emphasis in AI coming from an institution that has a really strong background in it was a big deal for me. I really believe that having that background is going to be really beneficial.

This interview has been edited and condensed for clarity.