print("Hello, world! 👋")

Thanks for landing here.

A short summary on how I got where I am now.

My first experience with programming was in secondary school.

If you ever wonder how to make someone hate programming, give them a task to build a calculator in C++. I consider myself a pragmatic person so the idea of building something that is not even remotely useful was not appealing. I have a calculator on my phone, PC that I was supposed to program one on, and a physical in my backpack, why waste time building another one?

Fast forward to university.

I studied economics with a desire to get into the world of big finances. After a finance analyst internship at Mastercard, I realised that I want to do something else.

  • The idea of staring at Excel sheets was not appealing. 😵‍💫
  • The urge to build something meaningful was stronger. 🛠️

I started to learn Python which I used to automate reporting at work. 🐍 I toyed around with few projects- not good engineering but I was learning.

Automating browser game from the childhood was fun. I’ve built a stock market simulation. Automating boring tasks at work gave me a sense of accomplishment and a higher purpose than crunching things manually.

At the time the idea of putting something bigger than a few scripts was not in sight.

I channeled my energy and made decisions to build experience in the world of Data- including analytics, engineering and data science. 📊 Almost 8 years, 3 companies and 12+ larger projects later, I felt a desire to document my journey and reflections.

I am hoping to solidify my knowledge and share my learnings. In the writing I am planning to focus on the fundamentals- so knowing specific tools is not the goal.

tl;dr: finance -> data analytics -> data engineering & data science -> data engineering consulting

Summary:

  • The most important thing so far was consistency & keeping it going.
  • Building pragmatic things that I like is what kept me going

If you are not sure where to start, start with something that you like. Kaggle has plenty of datasets that you can analyse as well as the community discussions on them. Automate the boring stuff with python (a great book by Al Sweigart) The barrier to entry is so much lower with the AI tools + technologies are changing super fast. So the best time to start is now!