August 4, 2021

Learner Spotlight: Data Engineer Student Veena Sanjeeve

Learner Spotlight: Veena Sanjeeve

Meet Veena Sanjeeve, a graduate of Dataquest’s data engineering career path. Two months ago, Veena started her new job as a Data Engineer at
a private IT firm. Here she works with distributed systems on AWS.

Here’s her story . . .

Q. Hey Veena, tell us a bit about your background …

I’m rooted in CS. I had a few credits under my belt, SQL was my core strength, and I was doing great at
my tech job. But then, life happened.

My kids are as old as my career gap — 8 years. And I’ve enjoyed every bit of it.

Q. How did you learn about Dataquest?

Early in 2020, I was trying to restart my tech career but in the data industry. I was researching for top
quality courses when I discovered Dataquest and started with the Data Analyst in Python path.

Q. How did you get into Data Engineering?

As I progressed along the Data Analyst path, I started getting super comfortable in Python. That’s when I
got more and more curious about the back end. I wanted to know answers to questions like:

  • How truthful is data?
  • How is data sourced?
  • What makes them fast?
  • How do systems get real/near-real time data?

It was a pleasant surprise when I discovered that Dataquest allowed me to check out all their courses in
the Data Engineering path! All I had to do was just switch paths to take a peek, and return to my original path.

This is when I understood that Data Engineering was what really quenched my thirst.

Q. What’s your favorite thing about Dataquest and why?

I have a lot of favorites:

  • No-video, in-browser coding is awesome! I don’t have to pause, rewind, forward. Also, I appreciate
    that I didn’t have to hook onto my headset.
  • Many awesome projects to try! Learning by doing builds solid confidence. These are not just projects;
    they use real-world data sources and trends.
  • Helpful and vibrant users in the community.
  • Opportunity to help others that’ll help thyself. (Never underestimate this! This is an awesome
    feature that helped me build my online data-footprint where one company’s department head found my SQL helpful
    and found me on GitHub via DQ’s profile page) Until then, I had no idea it was google’able! Imagine the
    opportunities this can entail? I had to ask, how did you find me?

Q. You got your current job offer before you even finished the Data Engineering path. Can you
share how you went about the job search process?

While I was still actively learning, I read an article on the Dataquest blog encouraging learners to
circulate their CV while they’re still taking the course. That made sense to me.

So, I circulated three versions of my CV — one as a Python Programmer, another as a Data Analyst, and one
for a Data Engineer.

At first, I shared only on LinkedIn to see how it would go. But then I shared it on Dice as well. That’s
when the opportunities started to roll-in and my recruiter found me. My recruiter found my Data Analyst CV, but I
got into a Data Engineer role when I mentioned that I was currently working on Data Engineering path at Dataquest.

I didn’t have to reach out for any referrals.

Q. How did participating in the Dataquest community help you in your job search?

The Dataquest community gave me the
opportunity to help others. This helped me build my online footprint.

So, when a recruiter approached me and said that I only have one year of experience I could say, “Take a
look at my GitHub and my online-footprint at Dataquest.”

There are quite a few recruiters who know how to fish out talent not according to years of experience but
based on quality of work a candidate has done.

Q. What are some of the things you learned at Dataquest that have helped you at your

  • Having a good understanding of most of DQ’s DE material gave me an edge in understanding how
    distributed systems sing. A major step in this was the multiprocessing module. It was a gold mine for me, and it
    still is.
  • Apart from this — Git, command-line, Time & Space Complexities of Algorithms (it makes me think twice about using
    nested for loops and extra variables), recursion, SQL-vulnerabilities, Least Privilege Principle, and the concept of DataFrames.
  • I also learned a great deal just by thinking how to respond to queries in the Dataquest community.

Q. What advice would you give to learners who are just starting out?

  • Grit pays off! There will be ups and downs while learning and job-searching. Patience and grit are
    best friends.
  • Maintain a quality portfolio. Jupyter Notebooks are your real certificates. You don’t have to do
    every project under the sun. Pick ones that many haven’t ventured into and personalize them.
  • Also, I can’t stress enough on quality code and meaningful comments, including naming convention.
    These should become a habit.
  • Finally, be creative with job search; tell the truth and stand out. There is no one size fits all.

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About the author


Dataquest teaches through challenging exercises and projects instead of video lectures. It's the most effective way to learn the skills you need to build your data career.

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