Uplimit (formerly CoRise) Co-Founder and Chief Product Officer Jacob Samuelson recently spoke with Uplimit alum Zoe Liang (formerly with healthcare startup Wellthy and currently with software development company Hightouch) about her time spent in the Uplimit Analytics Engineering with dbt course and how it helped propel her career trajectory from a data analyst to an analytics engineer with two well-known tech companies.
The following excerpts from Jacob’s conversation with Zoe have been edited and condensed for clarity.
Jacob: I’m so excited to talk with you. When I saw you had a new job, I really wanted to learn more about it! There are a lot of different reasons that people take our courses, but one of them that's very important to us is when learners start thinking about taking the next step in their careers. I wanted to learn a little bit more about how that looks for you. To start off, how did you find out about the course and how did you decide to take the course?
Zoe: Actually, it was recommended by my former manager, Kelly Burdine. She's a very active member in the data community. I think she knows Emily Hawkins, the instructor of the ‘Analytics Engineering with dbt’ course. She heard great things about this course, and thought that I could benefit from taking it because the data team at Wellthy was very small at that time. We only had one data engineer and one analyst — which was me — so we had to support the whole company's data requests. She thought that if I learned how to use dbt, I could support the engineer, as well as unblock myself. I took a look at the course website and thought it looked like something that aligned with my learning goals and would be a perfect course for me as an analyst.
I really enjoyed the course- everything was very smooth, and also very “user-friendly”. As an analyst, I did not have a heavy engineering background but was still able to catch up with the course content. I learned a ton, not only from the instructors, but also from my peers- the weekly code reviews were my favorite sessions. After completing the course my overall knowledge, not just about dbt, but also data modeling and engineering best practices in general (i.e. version control etc.) has leveled up a lot. I would say I feel very lucky that my former manager recommended this course to me.
Jacob: Yes, that's awesome. Maybe just taking a step back, how did you become an analyst? What was your background? How did your career start in that way?
Zoe: I actually started without any technical background, my bachelor’s degree was in international business. In college I had a few internships that involved some data analysis tasks, which led me to wanting to know more about data. So, I applied to a master’s program in business statistics. That's where I learned SQL and Python. After graduating, I landed my first job as a marketing data analyst. I was mainly helping the marketing team with marketing analytics, such as evaluating marketing campaign performance, helping design marketing strategies, and tracking competitors’ pricing, etc. It was this role that solidified my coding skills. I then joined Wellthy as a more generalist data analyst. I was the only data person there for about three months, before we had our first data engineer join. For a while it was just the two of us supporting all the data requests for the entire company.
Jacob: How big is Wellthy?
Zoe: About 300 people, and the main stakeholders for our team were the Client Success and the Coordination teams.
With the data team being so small, you could imagine my (and my team’s!) capacity at that time was pretty limited. As I mentioned earlier, that was one of the main reasons why I took the course so that I could really just unblock myself and deliver more for my team.
Jacob: Give me a little more of a sense with Wellthy, such as what work were you doing and supporting for the business?
Zoe: Wellthy is a caregiving support service company. A company’s employees can use Wellthy as a covered benefit to help their family, let's say, find childcare or in-home support. Wellthy helps find the caregiving services that best match the employees’ needs.
Jacob: You're an analyst and you are taking the course to potentially unblock yourself so you don't have to rely on the data engineer for data modeling. Maybe you can scale yourself because you have 300 stakeholders. Then you took the course and it sounds like you had a really good experience. So tell me, did you take the course knowing you wanted to transition into analytics engineering or how did that process happen after you took the course?
Zoe: Yes, great question. At first, I didn't really think about transitioning as I was happy about being a data analyst. After taking the course and having more discussions around analytics engineering (with the alumni community and the guest speakers), I started to feel that analytics engineering was actually a direction that I would be interested in and might be a better fit for me. I wanted to be a full-stack analyst so that I could streamline and apply my domain knowledge and analytical skills to the development process of the data products.
Jacob: That's awesome. Would you say the course helped you prepare for interviewing?
Zoe: Yes, definitely! For one, the course itself already helped me build a solid knowledge foundation of dbt and data modeling, which is the core requirement of an analytics engineer. In addition, the course community really deepened my understanding of the modern data stack and the modern data team. This in turn shifted my mindset from a “traditional data analyst” to a “modern data practitioner”. Oh, and I mentioned Uplimit in my cover letter as well. :)
Jacob: In the interview, what kind of stuff did they cover? Did you have to talk about why you're interested in analytics engineering or your experiences? What kind of things did you have to talk through?
Zoe: In my experience, normally during the first round (either with the hiring manager or with a recruiter), they would ask why I was interested in becoming an analytics engineer and which parts of my experience as a data analyst helped me with that transition.
The technical round normally consisted of coding, modeling, or analytical problems, such as: a live coding session, refactoring a data model, or solving a data problem, etc.
Normally after the technical round, depending on the company, there would be another panel interview with data team members/stakeholders, and a final round focused on culture fit.
Jacob: That's so great! Tell me about your role now as an analytics engineer. Now that you’ve achieved such a cool goal, what do you work on?
Zoe: As an analytics engineer, I own our full data stack from data ingestion to data reporting.
I’d say 80% of my work is focused on data modeling, documenting, and building dashboards/metrics. The remaining 20% is aligning with stakeholders to make sure we are tracking the metrics that are most important to the business, and to keep an eye on all of the possible data issues to make sure everything works smoothly (and accurately!).
Jacob: It's great to hear that you have a new role and the course helped you to get there. It makes us very happy to see that. What's next for you? Or do you have anything else you want to learn? If you could dream up the perfect Uplimit courses what would they be?
Zoe: I’m interested in taking the Dagster Course and hope to see more data engineering courses with Uplimit!