My Story and Why I Write About Data

*Hint* it's pretty untraditional & required going above and beyond

I’ve shared glimpses into my background and how I’ve broken into tech, but I’ve never told the story from start to finish. I figured, why not introduce myself more here?

My name is Madison and I’m currently an analytics engineer at Winc, a wine subscription company, as well as a technical writer. I’ve always loved math as it was my favorite subject in high school. I thoroughly enjoyed walking through complex calculus problems (am I crazy? maybe!), feeling so satisfied when I would solve them.

I’ve also always had an entrepreneurial spirit. Before I was even a teenager I started multiple businesses, always trying to sell something to someone in my family. I created purses using fabric scraps and a stapler, wrote my own newspaper, walked dogs, ran lemonade stands, and even baked cookies for my dad’s coworkers’ dogs.

Going into college, I wanted to learn more about business but also wanted to challenge my love of math. The college I attended was one of few to offer a Mathematical Finance major. This allowed me to take business classes as well as advanced math classes. The best of both worlds!

I also double majored in marketing because it was something I had always enjoyed. My second year in college I earned an internship at a sustainable fashion company working in social media. It was always my dream as a kid to work in the fashion industry, so I thought an internship was the perfect way to test it out.

While it was a really fun job, I didn’t feel challenged enough. I started talking to other teams within the company and someone introduced me to data science. I had no idea what this was at the time but I became obsessed. I started attending free data events in the city including hackathons, recruiting events, and workshops.

I quickly realized that this was something I wanted to do. While I didn’t want to change my major to computer science, I added on a data visualization minor to help me learn some R and Python skills. I also began shadowing a graduate course on Tableau so I could learn the tool. I really put myself out there to learn all of the skills I needed in the cheapest way possible. While every other senior was taking scuba diving classes, I was taking computer science level one classes (which are some of the hardest ones!).

The summer before my senior year, I attended a women in tech hackathon sponsored by Capital One. It was a beautiful June day and I almost didn’t go because I was planning on meeting up with my cousin for dinner. Good thing I did because a recruiter reached out to me with an opportunity to interview for a coding boot camp they were sponsoring.

After multiple interviews and being flown out to Virginia, I received a call saying I had gotten the job! It was an amazing offer and gave me the opportunity to learn to code for 6 months and then transition into a data engineer role within the company. It was honestly a dream. I was learning the skills I always wanted to learn and being paid to do it!

After vacationing for two weeks in London, I moved to DC to start my first big girl job. I made some amazing friends and learned so much during that bootcamp. After 6 months, I transferred into a DevOps role. I knew going into it that it wasn’t going to be the role for me but I embraced it and tried to learn all that I could. I developed my Python skills and became certified in AWS. Luckily my managers were very understanding of the types of tasks that interested me.

During this role, I was introduced to writing on Medium. We had an awesome content program within the company that allowed me to write articles and publish them on the Capital One publication. This is when I discovered my passion for making tech accessible to everyone! There was nothing out there that broke down super technical concepts into information that anyone could understand.

After that year was over, I transferred to another role that was more along the lines of what I wanted to do. It was still considered a data engineering role but it was here that I was introduced to dbt. This team wrote lots of SQL and utilized dbt to test and automate data models.

I really enjoyed the challenges that came with this work but realized it was time to switch to a company that allowed me more creative freedom. I wasn’t receiving the business exposure that I wanted. I also missed the energy of small start-up companies after interning for a few throughout college.

When I was searching for jobs, I knew I didn’t want a data engineering role again. I needed more creativity and wanted to interact with stakeholders. I tried applying for data analyst roles but wasn’t having any luck.

Then, I came across a job posting for analytics engineer which I had never heard of. After reading the description, I realized that this was the exact role I was looking for. It required some of the more technical skills that I had from data engineering but allowed for more cross-collaboration and creativity.

If you’re curious about the specific differences in the roles of data engineers versus analytics engineers, check out this article I wrote for ThoughtSpot.

I ended up interviewing with Winc, who was rebuilding their entire data stack. I was the second employee hired onto the data team and had the opportunity to make key decisions for the future of Winc’s data. My manager and I worked together to decide on modern data stack technologies such as Snowflake, Fivetran, and dbt.

Ever since, I have been writing about my experience as an analytics engineer and the things I’ve learned along the way. It’s been amazing to interact with so many cool companies and people in the space. There definitely aren’t enough female voices in the data space!

There’s also not enough “approachable” content. Coding tutorials and data deep-dives are often written at such a high level that beginners can’t follow along. I try to explain every little detail so that everyone can understand the topics I write about. Most of the time, complex concepts are better absorbed when there isn’t tons of technical jargon thrown in.

So, I will continue writing what I learn about on my path of analytics engineering. I hope you continue to follow along and learn new things!

Key take-aways:

• Test out different careers until you find one that works for you

• You never know what opportunities you could get just from showing up

• There are enough free resources out there to learn something new

• If you’re unhappy, don’t give up until you find happiness

How did you get started in data? Do you come from a traditional background, or something more untraditional like mine?