Young Mavericks’ Yaleesa: “My mission? Shaking up the IT world.”

Yaleesa’s (28) interest in the wonderful world of machine learning was peaked at the end of her BA in Information Science. Yaleesa: “For my ambitious graduation research, I was looking for an answer to my specific problem and ended up with a supervisor.He convinced me of the unique potential of machine learning. Although I quickly discovered that machine learning is no walk in the park, I feel at home in the IT world – and more specifically with Young Mavericks.”

Merging Passions as Data Engineer

Yaleesa spends her spare time gaming, writing codes for her own projects “and reading, especially technology stuff – ultra nerd alert!”. During her studies, Yaleesa worked as Python Developer on the design of various information systems. “I was looking to combine my passion for developing programs with the future possibilities of machine learning and landed on Data Engineering.” She instantly knew she had found her dream career but soon ran into another problem: “I started to doubt my abilities. Machine learning is very mathematical, and that’s not necessarily my forte. And not just that – as a recent graduate, I lacked experience with large complex data systems, which every Data Engineering vacancy required.”

Just as Yaleesa was second guessing her career choice, she came across Young Mavericks’ Data Engineering traineeship. “It was the perfect solution! The Young Mavericks traineeship allowed me the time and space to gain specific expertise, receive professional guidance and develop myself within a professional environment. I have learned to manage resistance, how to present myself and acclimate to the daily rhythm in a company. I now know that a successful Data Engineer needs more than specialist knowledge and passion for computers: self-confidence and assertiveness are essential, as is the art of taking others along in the process.”

Starting Out as a Young Mavericks Data Engineer Trainee

Yaleesa felt at home instantly with Young Mavericks. “The first period was tough but fun. The atmosphere at Young Mavericks is open, professional, ambitious and flexible. Nobody at Young Mavericks cuts corners. It felt good to not just be welcomed, but needed. Within just a few days, I felt like I had known my fellow trainees for years. Working together went smoothly and it was nice to feel supported while learning difficult subjects.”

At the beginning of her first project, Yaleesa found it a bit exciting, because it was a bit different than she was used to before. “Studying and working part-time lends itself to flexible use of time. I have ADD and I noticed quite early in my studies that my concentration improved significantly during the quiet evenings. Switching to firmer working hours had its challenges”

Fortunately, the Young Mavericks team was very involved; everyone invests a lot in their fellow employees and trainees. I was never alone and always supported – a feeling I’d like to give back to the company.” What also helped her, were the topics covered during the traineeship. “The trainings resonated with me and it didn’t take me long to realize I had made the right choice.”

A Whirlwind in the IT World

Yaleesa has now gained experience as a trainee with various clients. “With my current client, I operate with one of the oldest, most complex and important systems in the Netherlands. My colleagues here are all specialists in their field, but sometimes face challenges in the rapidly evolving IT world. It’s my mission to open these professionals’ mindset to the latest developments in DevOps, machine learning and automation.”

One of the most important lessons Yaleesa learned during her traineeship, is being more patient. “I am by nature quite impatient. If I’m into something cool or important, it has to happen NOW. Often it doesn’t work that way in big companies. Things take a while and I cannot do everything on my own – I need others to start a bigger movement.” Yaleesa has learned to temper her eagerness. “I learned to use my impatience and passion proactively to shake things up a bit. I don’t always make friends this way, but I am often praised in then end because a lot gets done. I hope my whirlwind approach gets people to think.”

ELT, ETL and Data Pipelines: loading Data in an Automated Manner and how to do it yourself

My name is Don and I am something between a data engineer and a data scientist. I automate repetitive tasks, generate insights from the data, manage projects and I often help in an advisory role for these processes. I especially enjoy the creative process required to solve problems using data.

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Data Pipeline Implementation: how to do it yourself

These instructions build on what has been discussed in ELT, ETL and Data Pipelines. In that guide, we discussed the problems that arise in storing and using data for a company. In response to those problems, we introduced the concept of Data Pipelines, which helps the company become better aware of the data loading steps and incorporating these steps in the most optimal way to create a Data-driven Culture. We also discussed some specific tooling that can be used to properly deploy Data Pipelines. 

Now that we understand the concepts behind Data Pipelines, we will now apply them to implement a functioning Data Pipeline. Just like most of our data engineering processes, we follow a step-by-step plan and provide an implementation strategy for each step. 

Hopefully a step-by-step plan will give you a solid foundation when you are constructing your own Data Pipeline as well as the implementation methods.  You can find the whole code on our Giftlab.

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