VP at Zinnia | When Does AI Actually Earn Trust in a Data Org?

What does it take to scale a data science and engineering team from 5 to 20 people in a single year — while also navigating the chaos of AI adoption in a space where the data has to be perfect every single time? Dustin Tucker, VP of Data Science and Data Engineering at Zinnia, joins Tech Teams Today for a grounded, no-hype conversation on building data teams, leading through change, and the leadership mindset shift that took him years to figure out.

Dustin has a contrarian take that will rattle a lot of engineers: stop bringing him solutions. Bring him the problem.

*What you'll learn:*
- How Dustin structures his data engineering team — client-facing, foundational, and an emerging analytic engineering function
- Why he scaled from 5 to 20 engineers in one year and what he learned about hiring fast without sacrificing quality
- The short, hard skills test approach to hiring that cuts through AI-assisted resumes and keeps the bar high
- Why he refuses to bike-shed on AI tools — and how focusing on Snowflake Cortex and DBT Copilot is driving real outcomes
- The ROI equation he runs on every AI project before a single token gets spent
- Where AI trust actually stands in a data org where client-facing output has to be perfect
- How AI has changed his day-to-day as a leader — and where documentation and follow-up have gotten a serious upgrade
- The leadership framework from Situational Leadership II that he still uses to diagnose every struggling report
- Why the best thing he ever did as a leader was learn to meet people where they are instead of expecting them to meet him
- His advice to aspiring leaders: there is no template, it takes time, and that's okay

*About the guest:*
Dustin Tucker is VP of Data Science and Data Engineering at Zinnia, a technology company transforming the life insurance and annuities space through data, automation, and AI. With nearly 20 years of experience across Fortune 500 companies, including Lowe's and Disney, Dustin has spent his career building data teams before the field even had a name — and leading them through every technology shift since.

*About Tech Teams Today:*