How Dataquest Made the Difference for Stacey’s Data Job
Today, Stacey Ustian is a data engineer. But the path that led her here wasn’t always easy, and there were a few bumps and twists along the way.
Her journey to data science started in a rather unusual place: the law library.
After earning her Master’s degree in Library and Information Science, Stacey had taken a job working in the library of a law firm. But she discovered she liked the working-with-information bits of the job more than she liked shelving books, and after a few years she transitioned into a role as a research analyst at another firm.
I came across Dataquest and checked it out. That was a turning point for me, honestly.
“That job was 50 percent qualitative research,” she says, but “the other half was quantitative data analysis using Excel.”
“I got really excited about those [Excel data] projects. I found that was the stuff I really liked doing,” she says.
Her husband, a data scientist, recommended she start learning SQL to expand her skills. After some Googling, Stacey found a learning platform — not Dataquest — and started studying SQL and Python.
But there was a problem.
“I got the basic syntax down, but I found that I had a lot of trouble when I went to start a data project on my own,” she says. “I just didn’t really know how to get started, what to do, et cetera. It was pretty frustrating.”
Another problem: in her job as a research analyst, she wasn’t going to be able to apply any Python or SQL skills she did learn. That job didn’t require anything beyond Excel. Stacey wanted to go bigger.
So she took a leap of faith.
“After some soul searching,” she says, “I decided to leave that position and then devote myself full-time to just learning all these technical skills that I would need to get a data analyst job.”
All-In on Learning Data Skills at Dataquest
“At that point,” she says, “I knew that this other [learning] platform was not the one.” So she began searching for an alternative. Eventually, she found Dataquest.
“That was a turning point for me, honestly,” she says.
“I went back and started re-learning Python and SQL on Dataquest. In addition to teaching me the syntax, [Dataquest] taught me the theory and the ideas behind what I was typing, which just gave me a deeper understanding of things.”
It also helped, she says, that Dataquest frames its lessons in the context of what working data analysts, data scientists, and data engineers actually do.
“[Dataquest teaches] how you would use this in the world of data analysis,” she says. “That was truly what I needed at that moment. That was the exact type of information that I was looking to learn and it was just perfect for me.”
So she went all-in. “I just full-time plowed through the Data Analyst path in, I don’t know, something like two and a half months,” she says. “I was doing it eight hours a day.”
And it worked. “I finished the path,” she says, “and when I then spent the subsequent months doing data projects on my own, I found that I knew where to start and things to think about and ways to approach different problems. That was all the stuff that I had learned in Dataquest.”
From Analyst to Engineer
Stacey’s intention was to find a data analyst job. So after she put together a portfolio of projects, including one of Dataquest’s SQL guided projects, she started looking for data analyst jobs.
To her surprise, an outside recruiter contacted her on LinkedIn about a data engineering role. “I went through that interview process,” she says, “and it turned out they were just really looking for someone that had an understanding of Python and SQL and that was willing to learn what they needed to learn in this data engineering role.”
When they offered her the job, she took it. “It’s perfect,” she says, “because I know that Dataquest just launched that data engineering path.”
“I’m like, ‘Well, I know what my next task is: start that and learn data engineering,’” she laughed.
One lesson from Stacey’s story, she says, is that you shouldn’t get tunnel vision and focus exclusively on jobs with a specific job title. “If at all possible,” she says, “search more on keywords in job descriptions. I applied for and interviewed for a lot of different jobs that weren’t ‘data analyst’, but they were data analysis jobs.”
Be aware that your data skills can open many doors, including some unexpected ones. “Knowing complex SQL queries can get you a lot of places, honestly,” she says. “You just never really know.”
Another, she says, is knowing your own learning style. “I don’t learn by videos,” Stacey says, so she knew to choose a platform that didn’t teach through video.
“I would recommend taking time to really understand the different platforms out there and which one is best,” she says. “I, of course, think Dataquest is best,” she adds. But there’s no one platform that’s right for everyone, so knowing what works for you is a good place to start.
She also says that holding yourself to a study routine is key. “I kept a working schedule,” she says. “I’d work in the morning, take a lunch break, and then work in the afternoon.”
And while not everyone can put in as much time as Stacey did every day, she says Dataquest is well-suited for folks with busier schedules, too. “Dataquest is broken off in smaller chunks, so it’s really conducive to that. You only have an hour, okay, well, just do one or two sections and that’s fine. It’s just about carving out whatever time you can.”
Finally, she says, know going into your job search “that you’re going to have to deal with rejection and that’s normal and everybody goes through it. Don’t let it discourage you, keep going. I applied to, I think, 115 different places before I found something.”
For Stacey, the destination has been well worth the journey. She’s now working as a Data Engineer at an enterprise marketing technology startup in New York City.
And of course, she’s learning more data engineering skills! As of this writing, her last login to Dataquest was yesterday.
Charlie is a student of data science, and also a content marketer at Dataquest.