Deji started solving computer-related problems as a Kid, and started writing code in the university. In the course of his interesting career, he's worn many hats - developing frontend, backend and hybrid applications, before transitioning into Data Engineering.
How did you get into Tech?
I would say my tech journey started way back as a kid when we got our first PC. I was glued to it all the time and became the de facto computer operator at home, always hacking around.
Writing code started in my second year at the Obafemi Awolowo University, Ile-ife, Osun State (OAU). We had a great tech community, and that helped motivate me a lot.
I participated in programming competitions and picked learnt to program with the Angular framework so I could build web applications. I did my first internship at Colab, another place with an amazing community where I met Robert who mentored me in Data Science at the time. Since then it has been one amazing opportunity to the other.
Why Data Engineering?
One definition that I love is this: "Data Engineering field could be thought of as a superset of Business Intelligence and Data Warehousing that brings more elements from Software Engineering" Source. This definition captures it for me. I like that I can build solutions that enable the business to derive impact from data and the problems that need to be solved are dynamic which makes it even more interesting.
What inspires you?
I am inspired by people who enjoy leaving their comfort zone and do not mind venturing into the unknown. For me, the unknown could be anything e.g a new problem I have no answer to. Being able to get to a point where I solve that problem gives me the energy and determination to keep pushing.
Which of the technologies you currently work with excites you the most, and why?
BigQuery, Google Cloud's petabyte-scale data warehouse. I work with it daily and it is a really powerful tool. From being able to perform transforms (ie the T in ELT), to analyzing massive datasets in seconds, and building machine learning models right from your data warehouse. BigQuery simplifies my daily work and enables me to achieve more in a short time.
What problem does it solve?
BigQuery solves a lot of different problems. To name a few, it helps the Data analysts query and analyze data for reporting purposes. It helps me as a data engineer perform transformations on massive datasets in a declarative manner. It helps the software engineers perform data exports which would be too much for transactional systems to handle and also one-off heavy computations needed by transactional systems.
Tell us about your growth.
I wear many hats 😅. I started out building frontend applications and subsequently moved on to backend development. I deployed a couple of hybrid mobile applications at some point.
Nowadays I work as a Data Engineer with a lot of interest in cloud technologies. It's being able to adapt and pick up whatever is necessary to get work done.
What does the future hold?
Building a (my 👀 ) unicorn company.
Tips for budding Data Engineers?
Learn fast. There are many engineering areas to cover, domain knowledge to acquire, tools to grasp and data systems to understand. Data Engineering is also a domain where things evolve quickly so it is crucial to be continually learning new things.
Understand that business knowledge is as important as technology. This would help you interpret what the stakeholders require quickly and prepare your systems in place to accommodate evolving requirements.
What have you been working on lately?
Customer segmentation using unsupervised learning with BigQuery ML.
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