A blog about working as a trainee data engineer at Datalab from an unrelated background.
Ecologist with a particular interest in data
The first three weeks at Datalab are behind me. As an ecologist, I have been immersed over the past period in a world that was (largely) still unknown to me. Before I started at Datalab as a trainee data engineer, I worked as a Nature Conservation Act supervisor at the RUD Utrecht. Although during my studies in Utrecht I already had some experience programming in 'R', in 2019 I truly started using it frequently. After working through the book 'Python for the absolute beginner', I then completed several online courses. Soon I wanted a kind of fusion between this new 'hobby' and my then work as an ecologist.
The practice
The first weeks are all about learning new things. So many new things that it is sometimes difficult to concentrate properly on one subject. From mutating databases in SQL, working with Git, to building dashboards in R Shiny. Fortunately, all programmes and languages work with logic. This is of course not always the same, but once you learn to work in different systems, you notice that you can increasingly think in new systems more easily. The foundation is actually the same in every discipline: immerse yourself in the subject with books for example, practise with the available training material, and follow the in-house training days to tie the loose ends together. And then - then the most enjoyable part begins. To truly make everything you have learned your own, you need to start applying it. For me that mainly means a lot of trying, making notes, and yet again consulting 'Stack Overflow'. Although my new colleagues are of course happy to help, it is sometimes difficult to find the balance between figuring things out yourself or asking that colleague who may be busy.
At Datalab you are expected to get on with it yourself. You are largely responsible for your own learning process as well. This motivates me: at Datalab they have confidence in my abilities - that I may figure things out myself first, and if that does not work, I can ring the bell without hesitation. Datalab works largely with fixed structures. Every week we discuss the completed and planned tasks of all my colleagues. This way you know what everyone is working on and you learn a lot from things people run into. Of course we then also discuss the solutions. Tasks follow from the PBS (product breakdown structure) drawn up based on the client's wishes. This way we divide larger assignments into more manageable pieces. Additionally, we are collectively alert that everyone continues working according to the agreed structures. That way things remain organised and I can keep the bigger picture in view. Fortunately, as an ecologist I am used to that.
I will regularly blog about my experiences as a trainee at Datalab. In this way I want to involve my readership in my work as a data engineer at Datalab.