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The Evolution of Data Roles
What I wish the future generations of talents will keep in mind
As ChatGPT is taking the internet by storm and getting everyone talking about which engineering jobs will be transformed by powerful AI, it’s easy to forget that many roles are already undergoing transformations. The label “data scientist,” for instance, despite being fairly recent, has little to do today with how the work was seen ten years ago.
Let’s review how learnings from the past can or cannot be applied to the future within the broader family of data roles. In the rest of this article, I’ll use interchangeably terms like “data engineer” or “data nerd” when referring to the global set of roles that put data at the core of their missions (let’s name a few together and appreciate for a second the richness and beauty of the data landscape: BI engineer, product analyst, data analyst, data scientist, product scientist, data architect, DBA, etc.)
From Hadoop and HBase…
Let me start with the journey I know the most: mine. My first permanent research and development role brought me to a governmental institution building its big data stack from the ground up. The challenges around operating such platforms at a large scale were barely known then (~2010), but the buzzword was already ubiquitous. The team…
