Data engineering has become an indispensable function in most software engineering organizations today. Data engineering as a discipline has broadened to encompass all practices, systems, and architectures involved in storing and serving data for a myriad of needs. From OLTP systems that power user experiences to the analytics systems that power business & user insights to all of the connective tissue that keeps data consistent between these systems, data engineers have their hands full managing complex systems and architectures. The promise of the modern data stack was to simplify these architectures to reduce the operational burden many of us still wrestle with today. But, what really works? Which technologies and practices live up to their promises? What patterns and technologies have stood the test of time? What are some pitfalls that you need to be aware of? Come to this track to learn from data engineers facing & solving these problems today.