I've been working with Data for most of my professional career. Database setup, BI, Data Integration, Architecture, Management, Master Data, Governance, Quality, I've worked on all of it.

Between 2013 and 2019, I worked as a Data Scientist. I'm no noob to this, having started working with neural networks back in College (implementing backpropagation from a copy of Hinton's original paper), but the changes in the IT environment in this decade (cloud, social, GPUs, agile and DS) convinced me it was time to focus my efforts here again. Since 2019, I switched to Solutions Architect, first at AWS and now at Databricks.

Technology-wise, I have learned several languages, and I don't believe there is one top language overall - there are contexts and applications where things will be easier or harder with one specific language, but no "one size fits all". I've also used several types of databases, and I'll usually pick what I think is best for the specific case at hand.