As the data analytics space matures demands from the business for the products and services being generated has been increasing. There is a thirst and appetite for internal and external data and analytics outputs. However, we need visible platforms and the ability to orchestrate complex data pipelines to enable this growth and underpin the mechanism. Cue the emergence of the engineer. We started with the data engineer and have welcomed more specialised roles including the Analytics Engineer, ML Engineer and AI Engineer. Heavily leveraging from the IT side, these roles have evolved and are becoming integral to the business. How exactly is the engineer in the data analytics space evolving? How is this enabling reliable accessible, performant systems that are monitored appropriately? Can we look at team structures? Are there ways we can implement or better use the modern data stack? As an industry we’re maturing, we’re further specialising and we’re reacting to the demands of the business. We’re seizing the opportunity to create more value for our organisations! That’s what Felipe will discuss in this week’s podcast episode. Enjoy the show. Thanks to our sponsor Talent Insights Group! Read podcast full summary here.

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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