#88 Data Engineering and Data Engineers' Future in Data Mesh - Interview w/ Joe Reis

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/Please Rate and Review us on your podcast app of choice!If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereEpisode list and links to all available episode transcripts here.Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here.Links:Joe's LinkedIn: https://www.linkedin.com/in/josephreis/Ternary Data Website: https://www.ternarydata.com/Monday Morning Data Chat: https://anchor.fm/ternary-dataJoe and Matthew Housley's interview with Zhamak Dehghani: https://www.linkedin.com/video/event/urn:li:ugcPost:6915063013410582528/Joe's upcoming book, "Fundamentals of Data Engineering": https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/In this episode, Scott interviewed Joe Reis, CEO/Co-Founder of data consultancy Ternary Data, Co-Host of the Monday Morning Data Chat, and author of the upcoming book Fundamentals of Data Engineering.Some key points or takeaways specifically from Joe's point of view (not necessarily those of the podcast):Find quick, high-value wins. Too often people focus on the big wins and those become overly complicated and end up in failure.Most software engineers don't understand data well enough to be data product developers in data mesh, at least yet.Data mesh is a polarizing topic. And that makes sense as it is pushing boundaries. Many hope it can come to fruition but it is a bit of a utopian view.The future of data engineering is to move past managing pipelines to much higher-value work.Speed to achieving wins with data - with a clear return on investment and trust - is the first thing you should focus on. Get this right and you can have the "luxury" of building great data products.Joe started by discussing the kind of nebulous area within software engineering and data that data engineering has always played - sit between the source systems and the data output, converting the data in the source systems into something consumable for data users. Previously, that was mostly about making...