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How co:rise Helped Ben Wilson Land a New Job (and a Side Gig in Doodling)

May 19th, 2022
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Ben Wilson is an analytics engineer at Mammoth Growth, an analytics consultancy that helps companies get the most out of their data. He landed the role after taking the Analytics Engineering with dbt course with co:rise. While he had experience working with dbt as a data scientist at a prior company, Ben took the course to level up his analytics skills and gain more experience in different areas of the data value chain. We met with Ben to discuss his experience in the course and to hear what he’s been up to at his new job.

The interview was condensed and edited for clarity.

I know you recently started a big new job. How did the dbt course on co:rise help you land it?

As you know, referrals are super valuable when interviewing for a new job. They can also be challenging to get: you can either ask an ex-coworker who doesn’t really know what you’ve been working on, or you can ask your current boss, who doesn’t want to see you leave. The course brought together professionals from companies all over the world, and we got to know one another via study groups, breakout sessions, and collaborative project work time. I was able to grow the network of people who really understood what I was working on, and were able to talk about it without a conflict of interest. I also had a couple of people from the course serve as my referrals, which helped me get the position.

The other aspect that really helped were the weekly projects. Each week, we were given real-world projects that challenged me to grow my skills. We were able to peer review one another’s projects so I was able to not only learn from building the projects myself, but from reviewing my peers’ work and from receiving feedback as well. By the end of the course, I had a more robust portfolio that I could point to as an example of my skills and I included this project in the github portfolio I used in interviews.

So tell us more about the job?

It has been a really cool step up in my career. I joined Mammoth Growth, where my job is to serve as a consultant to organizations that need help setting up their organization’s data systems and ultimately drive smarter data-driven decision making. The data teams typically consist of a senior consultant, a technical architect, and one or more analytics engineers, depending on the size of the engagement. It’s been really enjoyable because you get to work on different data systems, and you get to collaborate closely with the group of people that you’re working with.

As an analytics engineer on a data team, I’ve gotten to work with an e-commerce company, a B2B SaaS company, and a cryptocurrency exchange. It’s fascinating to learn all the nuances of these different businesses and also to see what stays the same. These businesses all require transparent and trustworthy data, so they can see what is working and what isn’t.

Let’s take a step back. Why did you decide to sign up for the co:rise dbt course in the first place?

Emily Hawkins, the course instructor, shares a lot of great information about data analytics on Twitter. She is a star in this field, and I really respect her contributions and engagement in the community. She announced that she would be teaching a course with co:rise and I was immediately interested.

When I started digging into the course, there were several things that really appealed to me: besides the opportunity to learn from Emily, I was really impressed by the roster of guest speakers. People like: Emilie Schario, Data Strategist in Residence at Amplify Partners; Niall Woodward, Data Engineer at Brooklyn Data; and Jason Ganz, Manager of Developer Experience at dbt Labs. Below is a sampling of the people involved in the first two runs of the course!

co:rise Analytics Engineering dbt guests and speakers

I was also compelled by the collaborative nature of the course. There are a lot of courses out there that let you take courses by yourself at your own pace. I wanted to take the course with others – so I could learn from them and also so that I would keep going, even if my schedule was busy.

How did the class match up with your expectations going in?

As expected, the instructor Emily, the material, and the community were all great. What blew me away, though, was the dedication of the staff. They were always there to help. If you missed a deadline, they would reach out to you one-on-one and discuss how to get you across the finish line for the course, and if you did something notable, they’d celebrate it in front of the entire class. That encouragement really helped!

I know you gave a talk to the cohort. Tell me about that.

That was definitely out of my comfort zone! The course staff asked the community if anyone wanted to volunteer to give a talk about their analytics engineering work. At first, I was hesitant because it can be an intimidating thing to volunteer for. The reality is that the analytics engineering discipline is new enough that everyone is still figuring it out. I realized that my experience would be relatable and valuable to others and I’m so glad I raised my hand.

In my talk, I shared my mental framework of how data, people, infrastructure, and modeled outputs come together to deliver value. It was really valuable to speak to a room of 30+ other practitioners who could give me live feedback. Though it was initially nerve wracking, it grew my confidence with respect to data engineering and more generally. I also made original sketches – one of my side hobbies – to bring my presentation to life. It was really a blast in the end.

Ben Wilson's data flow visualization

Can we spend 30 seconds on your doodling? It is amazing!

Writing helps me think clearly. I found doodling helps me get that same clarity. A few boxes and arrows can go a long way!

I made this one as a thank you to Miles Russell for his guest talk to the dbt class. His talk gave me a mental “aha moment” and I wanted to try to capture that in an image.

Ben Wilson's visualization of data modeling lecture from Miles Russell

Last question. What advice would you give to someone who hasn’t had their first analytics engineering role, and is looking to break into the field?

Analytics is not a theoretical discipline, and data is not that interesting without a domain. It’s best to pick a subject area that you enjoy and learn as much as you can about that area. Then, you can use your specific domain knowledge as a wedge into your target industry and your technical skills as leverage to crack that door wide open.

Additionally, get out of your comfort zone, and talk about your work with others! The analytics engineering course gives you a great network, access to thought leaders in the domain, and a public piece of work that you can share as an example of your skills. It’s a great way to demonstrate that you understand topics such as dbt principles, model layers and dbt tests, dbt macros, packages, and dags, and dbt exposures. Most importantly, it shows that you can overcome the challenges needed to get the job done. I highly encourage you to take it. And when you do, I’ll be in the community Slack, so say hello!

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