The Most Expensive Mistake (for now) I probably made the most expensive engineering mistake of my life. (Remind me in five years to revisit this post again if it’s still the most expensive one.) It was one of those incidents that rarely happen, the kind that throws you into
Last week, I spoke at a trivago meetup about SumUp's Data Mesh journey from the perspective of our Data Platform team. I highlighted a few non-technical changes we made along the way: ✅ Hiring and upskilling towards software and backend engineering, not just data engineering ✅ Doubling down on developer
I spend most of my day dealing with data platforms—SQLs, Snowflake tables, Kafka incidents here and there. Things that don’t really care if the button has rounded corners or not. But recently, I started vibecoding a passion project (more info soon). Not because I want to pivot into
Note: originally published in 2022 in my medium blog and still very relevant in the ever-evolving data space. In my last 3 companies, I started to get more involved in hiring Data Engineers. Every interview is different and unpredictable. But one thing is for sure, there is always a point
Big Data. This was the hot topic back then that a lot of engineers had to solve. When I started my career in 2012, processing terabytes of data was a challenge. We had limited compute power that could fit our on-premise setup. Nowadays, it wouldn’t be surprising to see
Presented in DataMasters Episode 9 : Data Journeys Unplugged How it started vs how it’s going I started my career way back in September 2012 as an Application Developer in IBM. I applied to 100s of jobs through jobstreet and monster. There was no LinkedIn before so we had to