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.
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- Your host as usual is Tobias Macey and today I’m interviewing Jigar Desai about building effective engineering teams
- 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?
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- 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.
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