The modern data team is undergoing significant changes in response to new tools and technologies. The shift towards cloud-based architecture and automation has made it easier for teams to work with data, reducing the workload of both initial setup and daily responsibilities. Automation is causing a philosophical shift toward treating "data as code," allowing for more flexibility and collaboration. Remote work is changing day-to-day routines, providing individual team members with more control over their time, while also broadening the talent pool. Traditional methods are on their way out, replaced by new workflows and increased innovation incubated from a larger talent pool. Data team roles are changing, with old roles becoming obsolete and new ones gaining prominence. Specialized roles are emerging, allowing for more focus on specific areas of expertise without worrying about the intricacies of data infrastructure. The purpose of a data team will continue to shift, requiring an easily adaptable data stack to navigate these changes. A new formula for data stacks is starting to shake out, with tools like Fivetran, Snowflake, dbt, Census, and BI layers forming a resilient and adaptable infrastructure.