Data Platform Engineer
I've always been drawn to the space where hardware meets software, where bits turn into signals and signals turn into decisions. That curiosity eventually led me to distributed systems and data platforms, starting with tools like Spark, Iceberg, Kafka, Doris, Trino, Flink, Airflow, and more.
Before data platforms became my focus, I was tinkering with microcontrollers and single-board computers, building small IoT networks over MQTT. Working with constrained devices and unreliable networks taught me how systems behave outside the assumptions of a datasheet. I also got into USB protocols and HID devices. There's something satisfying about writing code that talks directly to silicon.
That interest eventually grew into DevOps and Data Engineering. I've worked on databases, moved data reliably between systems, and built pipelines that scale and remain fault-tolerant across both batch and real-time workloads. Along the way, that has meant cutting cloud costs by up to half and scaling pipelines to billions of events a month.
I'm still happiest close to the metal, whether that's firmware, protocols, or the parts of a system that most people never see.
Why Every Data Structure Exists · Part 1
What a key-value lookup is, why hash maps answer it in O(1), and why the same operation behaves completely differently in memory and on disk.