If I were to name a favourite book, that would be Gibson's "Neuromancer"; hackers jacking into cyberspace by projecting their consciousness into a shared virtual space, a hidden layer augmenting the perceived reality. That was cyberpunk at its most refined form; brains interfacing with computers and enhanced cognitive capabilities. Now, I am positioned to realize the blur between science fiction and reality. Ideas and notions that were previously thought to be science fiction are becoming a reality, and that is something that overwhelms me.

Quoting Gibson, "My problem is that all things are increasingly attractive to me".
My unique interest and enthusiasm for Data Engineering (and ML as an afterthought) came organic from my previous professional experiences in SWE and my PhD research. Specifically, I tackled challenges related to analyzing big data in the latter one (Apache Spark enters the chat).

👨‍💻 My current role is Senior Big Data Engineer (DE).
🌍 Interested in green/energy tech and sustainability.

🐍 Python
🚀 Scala
🌊 DE — Azure/AWS and Databricks/Spark/SQL (batch & stream)
🤖 MLE — k8s/kubeflow and Tensorflow
🎯 Graph Theory
❌ C++/Qt — not anymore

🧠 PhD Candidate in Cognitive Neuroscience at Maastricht University; focused on Brain Connectivity (functional) & Network Neuroscience.

💁 drop out

🎓 In-depth theoretical topics on DE
🧊 Engineering tools; Flink, Iceberg, Nessie, Datahub, etc
🦀 Rust, Go, Mojo
🕸️ Graph databases like neo4j

☄️ Apache DataFusion + Comet
♻️ Delta + Deletion Vectors
🧂 Salting in Apache Spark
🤖 Getting Started with the spark-operator on minikube
✨ ⩵ Planning on Apache Spark ⩵
⎈ kubeflow on minikube — quick setup