Alumni Spotlight

From Test Engineer to Data Engineer after Jigsaw Labs

By Jess Feldman
Last updated on August 24, 2021

Although Chris Santos was skilled in hardware test engineering, he knew it wasn’t his long-term career path. His tendency to organize led him to data engineering at Jigsaw Labs! With its personalized teaching style and career support, Chris explains what set Jigsaw Labs apart from other data bootcamps. Now Chris is three weeks into his new job as a Data Engineer at NEAR, and he shares what to expect in the online bootcamp, the kinds of projects and labs he built for his data portfolio, and his tips for anyone considering data engineering as a career.  

You spent many years working as a Test Engineer — what inspired you to pivot into Data Engineering?

I was working in hardware, and although I was skilled at it and making good money, I didn't see a wealth of opportunities to advance my career. I was always interested in data and data analysis. As I was taking classes in data science and networking with people, I discovered data engineering and wanted to pursue it. Although data science is interesting, I wasn't particularly excited about it. As I got to know more about data engineering, it was pretty fascinating.

What is the difference between data science and data engineering?

In my experience, data science involves using Python and tools like Pandas to gather insights from data sets. Data engineering, on the other hand, is cleaning and organizing data to make it useful. I'm a neat person and I like organizing things – making data useful and readily available for customers and data scientists strikes a chord with me. Being an engineer myself, I understood the data pipeline and the flow of data. 

There are so many online data bootcamps now — why did you choose Jigsaw Labs?

I actually met Jeff, the founder of Jigsaw Labs, through a mutual friend. I gave him a quick call, and after 30 minutes, I thought, "Okay, Jigsaw Labs sounds legit." The tuition price seemed right, they have small class sizes, and the course delves into all of the topics I was interested in. The instructor was nice, and I felt like I could learn from him. 

Jigsaw Labs offers a job guarantee that within six months of graduating, a Jigsaw Labs graduate will land a job offer of $70,000. That guarantee made the price of the bootcamp worth it for me. 

What was the Jigsaw Labs application process like for you?

In a 30-minute call, we talked about my background as a hardware engineer. I had been doing Python for five years; not necessarily actual development, more like scripting. Jigsaw Labs felt like I had great building blocks to be successful in the data engineering boot camp.

What was a typical week like in Jigsaw Labs’ online bootcamp

There was a three-hour, live class session on Tuesdays and Thursdays and an eight-hour, live class session on Saturdays. The course is taught on Eastern Time, and I was on Pacific Time. When I first started the program, everyone in my cohort knew more than I did, but I had an advantage being three hours earlier which meant I could do the bootcamp, have dinner, and go back to practice everything that I learned. I would sometimes work until 3 a.m., not only because there was pressure to catch up but also because it was fun. 

What did you learn about data engineering in the Jigsaw Labs curriculum?

The bootcamp covered web dashboard topics, including Python (object-oriented, testing, Big-O, and data structures), SQL Query (SQLite3 and PostgreSQL), and Linux command line. We learned Restful API and ETL to Flask web app, Streamlit interactive web dashboard, Git and Github. On the DevOps side, we covered AWS (IAM, EC2, RDS), Docker, and Kubernetes. At the end of the bootcamp, we went over data management, which included Pyspark, OLAP vs OLTP, Airflow, AWS S3 and Redshift.

Did the teaching style match your learning style?

Jigsaw Labs has a particular teaching style that works. There was a solid hybrid approach to teaching and practice. The instructor will teach the material, then give us labs to complete. We would talk amongst ourselves, practice, and try to retain what we were taught. The course does move fast — many bootcampers had to take screenshots to keep up. We would split into breakout rooms so the instructor could check up on how we were doing. 

What kinds of data engineering projects did you work on for your portfolio?

Our instructor created the course to prepare students on how to build something from scratch. He takes you from the traditional way of doing things through the advancements in data engineering over the years, so there was a lot of cutting-edge tech that we got to learn. 

There was a data aggregation project where we collected data and stored it in our database. We then made our analysis and came up with predictions based on the data. In smaller projects such as labs, the instructor provides all the data you need so you could get used to the format. Sometimes he would give us the CSV to make it easier for us. The smaller projects feed into your final project, which you can use as a portfolio builder. 

Other projects were tailored to what interests you. While that's a good thing, it's also challenging because sometimes you have no idea what to do for your project. You have to do your research to see what you're interested in and what data types are available. 

My final project was focused on mobile gaming, specifically revenue and downloads. I was looking at whether there are indicators of how successful a mobile game app will be if there are ads versus in-app purchases. This project meant I had to make clients tap into APIs. Once I had access to the data, I had to do ETL to make the data fit the database without any tables. 

How did Jigsaw Labs prepare you for the job hunt? 

We learned how to prepare for the job hunt with coding questions, tips on how to break into data engineering, and interview preparation. Jeff, the founder of Jigsaw Labs, used to be a lawyer, so he counseled us on how to make the career transition into tech. Additionally, we had support in searching for jobs and looking for leads. Jeff put so many independent hours into connecting us with recruiters and employers to facilitate our personal job hunt. 

Which tech roles did you feel qualified to apply for after graduating from Jigsaw Labs?

​​I felt qualified for Data Analyst positions, DevOps positions, and of course, Data Engineer positions. For anyone just starting their data career, I recommend being open to whatever you can get, just so you can get experience. 

Congrats on your new role as a Data Engineer at Near! How did you land the job?

Near is a location-based data company that purchases location data, anonymizes it, and gives their clients insights into how they're doing in advertising and customer outreach. Near provides insights into how effective marketing strategies are in gaining foot traffic. 

I discovered this job through one of the Slack communities that Jeff connected me to. There was a hiring manager interested in finding candidates and I was one of them! The first interview was a simple phone call. The second interview involved homework and a skill assessment, which tested my ability to read/understand Python code and check for errors. It wasn't too crazy. 

What are you working on at Near?

I'm in my third week, so I'm still at the beginning stages. I’m crawling through code and handling smaller tasks while trying to understand what the code is saying and why it's scripted the way it's scripted. I'm getting used to AWS and Near’s framework, which was written by two people at the company. I now have an opportunity to improve the framework using what I learned at Jigsaw Labs while I’m getting up-to-speed. 

Being only three weeks in, I'm not utilizing everything I learned at the bootcamp yet, but because of my experience at Jigsaw Labs, I have a wide net of topics under my belt. If somebody told me that we are using Kubernetes, Docker, Docker, or AWS, I would be ready to jump in. 

What has been the biggest challenge so far in this career change?

Because I have been working for the past fifteen years as a hardware engineer, to start this new data engineering career, I took a significant pay cut. At the same time, I have a new passion for something that I want to learn. I know that as I grow, the salary will come. There are sacrifices that you have to make in any career pivot.

Do you have any advice for other engineers considering a career pivot into data engineering?

Start sooner, if possible. Chat with people in the field to understand what it's like to be a data engineer. I've been working in hardware for over a decade, but it wasn't my dream career. After talking with people about data engineering, I was more excited. Having a community of people you can speak with is crucial. Ask questions like, Is this a terrible job? or Is there a bright future for me in this industry? Exploring other people's perspectives helped me to shape my decision. 

Find out more and read Jigsaw Labs reviews on Course Report. This article was produced by the Course Report team in partnership with Jigsaw Labs.

About The Author

Jess is the Content Manager for Course Report as well as a writer and poet. As a lifelong learner, Jess is passionate about education, and loves learning and sharing content about tech bootcamps. Jess received a M.F.A. in Writing from the University of New Hampshire, and now lives in Brooklyn, NY.

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