Aura Minerals cut pipeline migration time by 87%, transforming a 45-hour manual process into a 6-hour lift with relatively little manual oversight. In this session, learn how the team used AI tools to accelerate their shift from a complex PySpark environment to a streamlined, modern dbt workflow. You’ll walk away with a clear view of the strategy, the tools they used, and what it looks like to modernize your data stack with AI as a force multiplier.

Daniel Avancini is the chief data officer and co-founder of Indicium—a fast-growing data consultancy started in Brazil.  There are a lot of data consultancies around the world, and a lot of them do great work. What has been so fascinating about Indicium's journey is their HR model. Rather than primarily hiring experienced professionals, they decided to go hard on training. They built a talent pipeline with courses and an internal onboarding process that takes new employees from zero to 60 over a few months. The result has been phenomenal and Indicium delivers great client outcomes, but most importantly, they're building skills for hundreds of brand new data professionals. Data is a hard field to break into because fundamentally you can't do the real thing unless you have access to data. So any company that is investing in building scalable hiring and training processes for analytical talent is one to be excited about. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.