Why I Chose to Become a Data Engineer
Image credit: Photo by Marco Aguiluz on UnsplashHow my experience working on projects for global tech giants sparked my passion for data systems and inspired my journey toward becoming a data engineer.
Starting from Real-World Data
Before I even began my Data Science degree, I was already working with data in practice.
I currently hold two roles that have exposed me to the scale and complexity of real-world data systems:
As a Search Engine Evaluator at Welocalize, I analyse and rate search results for what my teammates fondly call “the Big G” — the largest search engine company in the world. The work involves assessing data relevance, user intent, and content quality, giving me insight into how massive data pipelines fuel intelligent search systems.
At the same time, I work as a Data Analyst at Peroptyx, supporting “the A” — a major high-end electronics producer known for its focus on user experience and AI innovation, the one with the bitten fruit symbol (If you know, you know 😉). My role focuses on evaluating and annotating data used to train and refine machine learning models.
More importantly, these experiences opened my eyes to the hidden infrastructure behind AI and data-driven products.
That’s where my fascination truly began, not just in analysing data, but in understanding how data actually flows, scales, and becomes usable.
Discovering My Path: Data Engineering
While many people are drawn to the excitement of data science and machine learning, I found myself captivated by the architecture behind the scenes: the pipelines, systems, and transformations that make everything else possible.
I realised that data engineers are the backbone of modern data ecosystems, ensuring that every model, dashboard, and AI system runs on reliable, well-structured data.
That sense of building something foundational systems that quietly empower others resonated deeply with me. It’s not just about writing code; it’s about enabling data to move seamlessly across complex environments.
Studying with Purpose
To deepen my technical foundation, I’m now pursuing a Bachelor’s degree in Data Science.
In my first semester, I’ve chosen to study with a focus on identifying which courses directly support my goal of becoming a data engineer, such as Data Science Fundamentals, IT Infrastructure, and Information Systems.
This approach helps me understand how technical systems and data processes interact, even before diving deeply into programming or cloud tools. I’m not just learning theory, I’m learning how data systems work from the ground up.
Looking Ahead
My next goal is to strengthen my skills in SQL, Python, and cloud technologies, while applying what I learn through small-scale data pipeline projects.
I plan to keep blending theoretical learning from university with practical insights from my current roles, turning real-world observations into growth.
Becoming a data engineer is a long journey, but it’s one I’ve already started through experience, curiosity, and intentional learning.
This post marks the beginning of my journey as a future Data Engineer, one step at a time, grounded in real-world data and guided by clear direction.
Next Step
In the coming days, I’ll share my personal roadmap toward becoming a Data Engineer, a structured plan that connects my coursework, online learning, and practical experience.
It’s not just theory, but a direction I’ll continuously refine as I grow in this field.
