How And Why To Build Effective Teams As An Engineering Leader

The Python Podcast.__init__ - Podcast autorstwa Tobias Macey

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Summary Your ability to build and maintain a software project is tempered by the strength of the team that you are working with. If you are in a position of leadership, then you are responsible for the growth and maintenance of that team. In this episode Jigar Desai, currently the SVP of engineering at Sisu Data, shares his experience as an engineering leader over the past several years and the useful insights he has gained into how to build effective engineering teams. Announcements Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great! When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With their managed Kubernetes platform it’s easy to get started with the next generation of deployment and scaling, powered by the battle tested Linode platform, including simple pricing, node balancers, 40Gbit networking, dedicated CPU and GPU instances, and worldwide data centers. And now you can launch a managed MySQL, Postgres, or Mongo database cluster in minutes to keep your critical data safe with automated backups and failover. Go to pythonpodcast.com/linode and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it. Select Star’s data discovery platform solves that out of the box, with a fully automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day. Just connect it to your dbt, Snowflake, Tableau, Looker, or whatever you’re using and Select Star will set everything up in just a few hours. Go to pythonpodcast.com/selectstar today to double the length of your free trial and get a swag package when you convert to a paid plan. Your host as usual is Tobias Macey and today I’m interviewing Jigar Desai about building effective engineering teams Interview Introductions How did you get introduced to Python? What have you found to be the central challenges involved in building an effective engineering team? What are the measures that you use to determine what "effective" means for a given team? how to establish mutual trust in an engineering team challenges introduced at different levels of team size/organizational complexity establishing and managing career ladders You have mostly worked in heavily tech-focused companies. How do industry verticals impact the ways that you think about formation and structure of engineering teams? What are some of the different roles that you might focus on hiring/team compositions in industries that aren’t purely software? (e.g. fintech, logistics, etc.) notable evolutions in engineering practices/paradigm shifts in the industry What are some of the predictions that you have about how the future of engineering will look? What impact do you think low-code/no-code solutions will have on the types of projects that code-first developers will be tasked with? What are the most interesting, innovative, or unexpected ways that you have seen organizational leaders address the work of building and scaling engineering capacity? What are the most interesting, unexpected, or challenging lessons that you have learned while working in engineering leadership? What are the most informative mistakes that you would like to share? What are some resources and reference material that you recommend for anyone responsible for the success of their engineering teams? Keep In Touch LinkedIn Picks Tobias Bullet Train movie Jigar Top Gun Maverick movie Closing Announcements Thank you for listening! Don’t forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. The Machine Learning Podcast helps you go from idea to production with machine learning. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Links Sisu Data OpenStack Java The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

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