The business intelligence landscape has undergone significant changes over the past decade, driven by advances in technology and big data. The roles of Business Analysts and Business Intelligence Developers have evolved to accommodate this shift, with Data Scientists emerging as a new role that leverages Ph.D.-level statistical analysis to drive business decisions. The modern data stack has given rise to Analytics Engineers, who bridge the gap between Data Analysts and Data Scientists by maintaining flexible but clean data lakes and creating easy-to-process data pipelines. However, the lack of proper care for data lakes can lead to "data swamps," and without an intimate understanding of the data, incorrect metrics can be created, leading to a re-emergence of siloed IT departments. To overcome these challenges, organizations are adopting modern data stacks and leveraging tools such as dbt, Fivetran, and BetterException, which empower Analytics Engineers to do their job correctly.