A Short Journey From Industrial Engineering to Data Engineering
A Journey from Optimising Physical Systems to Building Data-Driven Insights
Hello everyone, whether you're deep in data or just curious about it! 👋🙂
Have you ever wondered what diverse backgrounds lead individuals into the field of data engineering?
As you may know, Pipeline to Insights was created by two data engineers who transitioned from analytics and industrial backgrounds to data engineering. In this post, we’d like to share the story of Hasan, one of the co-founders of Pipeline2Insights, and how he found his way into the world of data engineering, a path that wasn’t always straightforward, but one he has come to love.
Starting in Industrial Engineering: Exploring New Paths
My journey started with a bachelor’s degree in Industrial Engineering. During that time, I did internships and worked in different industries. These experiences helped me learn what I liked and what I didn’t:
Production Internship: I learned about manufacturing processes, but it didn’t excite me.
IT Internship in Database Engineering: This was a turning point. I loved working with databases and found my passion for data.
Planning Specialist in Retail: While it had its challenges, tasks like managing orders, budgets, and logistics of overseas stores didn’t inspire me.
Looking back, the time I spent working with databases during my IT internship planted the first seeds of my interest in data-related fields. But at that point, I wasn’t fully aware of how far down the data rabbit hole I would go.
Grad School: A New Focus Emerges
After my bachelor’s, I did a master’s in Industrial Engineering. I wasn’t sure what to focus on at first, but I got interested in data mining and data science. Working on data clustering and feature selection made me see that I wanted a career in data. It felt unplanned, but I was drawn to it.
Soon after, I got my first job offer as a Data Scientist at a startup. This was my official start in the data field and a big moment in my career.
Discovering My True Passion: Data Engineering
After my master's, I decided to pursue a PhD focused on Data Engineering, specifically in distributed stream processing systems. This was the turning point. Working in this field, I realised how much I enjoy the challenges of building data pipelines, optimising processing systems, and managing infrastructure.
This was when I knew, Data Engineering was where I wanted to be. It combines everything I love: solving complex problems, working with scalable systems, and designing solutions that make data truly useful.
Bridging the Skill Gaps: Challenges in My Transitions
Transitioning from Industrial Engineering to Data Science was eye-opening. Even with a strong background in advanced math, statistics, and optimisation, I discovered unexpected gaps. I hadn’t realised how messy real-world data could be, and a lot of my time went into cleaning it. Switching from Excel to programming languages for data analysis was also a challenge.🧑💻
The next transition, from Data Scientist to Data Engineer, brought its own difficulties. While I was comfortable with data processing, I needed to learn data modelling and software engineering principles. Concepts like version control, CI/CD, and efficient data modelling for scalable systems were all new to me.
Embracing the Journey Ahead
I’m now fully focused on data engineering and always trying to do my best in this field. Each day brings new challenges and chances to learn. I’m committed to improving my skills and giving back to the data community. That’s why I joined this channel, to learn and grow with all of you.
This is just the start, and I’m excited to see where this journey will take me next, along with all of you.
Next week, you'll hear the story of Erfan, the other co-founder of Pipeline to Insights, and learn how he gradually moved from a Data Analyst role to Data Engineering.
If you enjoyed reading this post and would love to another story, stay tuned by subscribing for our upcoming posts! 😊
Join the Conversation!
If you have a similar story or unique path into data engineering, we'd love to hear about it. Please feel free to share your experiences in the comments below!