Meet Gino Parages, a former sales and IT business analyst with no coding skills who decided it was time
to learn coding to give his career a boost. He chose Dataquest to help him achieve his learning goals and land the
job he wanted.
Here’s his story…
Q: First, what are your preferred pronouns?
Q: All right, Gino! What’s your current job title? At which company?
A: I am a Data Engineer – Client Reporting.
Q: Can you also tell us a little about the work you do at your current job?
A: Data Engineering: Python, SQL, Pandas Cleaning, PySpark. Data Science: Machine
Learning, Tableau, Google Data Studio, Dash/Plotly, Visuals, Data Aggregation. Solutions Delivery: Requirements Gathering, Requirements
Q: Now can you tell us a little about your background?
A: I worked at Pfizer for seven years. I always stayed in healthcare/biotech. I wanted
to code and move my career in a more technical/hands-on/individual contributor direction.
My work at Pfizer was: 3.5 years in sales and 3.5 years in IT as a business analyst/data analyst/data
engineer hybrid role but with zero coding. The last year became all coding and data wrangling/prep etc. The skills
from Dataquest made this very feasible.
Q: What made you get into the data industry?
A: The potential for future business, but also it’s just interesting. I love
spreadsheets. Why not learn to work with massive “spreadsheets”?
Q: How did Dataquest’s teaching methodology (no-video, in-browser coding) work for you?
A: It was great for me. I actually prefer this method. This is very important for me as
I liked to experiment on the Jupyter Notebook on the side as I went through lessons and understood
everything I read. It’s painstaking, but it made sure I was solid on the material.
Q: Which path(/s) did you do at Dataquest and why?
A: Data Scientist and some of Data
Engineer. I liked the idea of learning the math behind the data science path. I also wanted to make sure I got
a decent introduction to machine learning I could build from on my own with other resources I’m fond
Q: What’s your favorite thing about Dataquest and why?
A: Of the platforms I have used, Dataquest is the most difficult. I think the material
is very challenging where in others they basically hold your hand. The hand-holding makes it easy to fall into
patterns of “chill and watch”. If you want the job, you gotta respect the learning curve!
Q: Now can you tell us the story of how you went about the job search process?
A: I started looking for jobs after I had built out about eight end-to-end projects. I
wanted to make sure I had a GitHub repo that was not only for show but also that I felt like I could do the job. I
created challenging projects for myself and tried to cover everything I imagined an employer would want, using many
job recs as the benchmark.
I spent possibly three-four months working on my major projects while taking in content. I think the best
idea for me was to get used to the thought that I would not reach a point where content ingestion would end. After
that, I set my sights on completing my self-imposed challenges and allowing myself time to read, watch, and listen
to as much information as I could to build cool stuff.
Once this was done I felt comfortable taking on projects at my job. I reached out to teams and offered my
help. The team I was on had a full ETL request from an API external to the company. I accepted the request to
extract the data, transform, and then prepare for load. This was the final boost to, “Yes, I can do this!”
From there I used skillsyncer.com. I made custom resumes for every
job. I set my standards on what was feasible/salary/skills I wanted. Submitted to every single easy apply job, and
then submitted to more jobs . . . did that about four times. I went through about 15-20 interviews, minimum. Then I
found the gig I wanted and accepted the role
Q: What are some of the skills you learned at Dataquest that help you at your job?
A: Python, Pandas
Q: What advice would you give to Dataquest learners who are just starting out?
A: You need to understand that the idea of completing Dataquest will not give you enough
to get a job IF you are blowing through the material like the wind. This will require thought, responsibility, and
respect for the material. You have to take time and review the sheets, write notes, practice, and surround yourself
with information to make sure you are not confused before moving on. TAKE WRITTEN NOTES. USE JUPYTER NOTEBOOK!
Q: Finally, where can people find you on the Internet?
- LinkedIn: https://www.linkedin.com/in/ginop8/
- Github: https://github.com/eugeniosp3
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