Diving into Streaming Data Design Patterns for Delta Lake

​Are you wondering if general concepts like data engineering design patterns can help you learn about Delta Lake? Or, if it's possible to leverage Delta Lake within your streaming data architecture?

​In this webinar, Scott Haines and Bartosz Konieczny will answer these two questions. Scott, who gained streaming expertise at Yahoo, Twilio, and Nike, will share with you best practices for leveraging Delta Lake as a component of your streaming architecture. Bartosz, who recently published Data Engineering Design Patterns, will reverse-engineer a few of these design patterns to explain which Delta Lake features make everything tick.

​Speakers

​Bartosz Konieczny, Freelance Data Engineer, waitingforcode.com 

​Bartosz is a freelance data engineer enthusiast with 15+ years of hands-on experience on the projects from various industries that helped him work on many data engineering problems in batch and stream processing, such as sessionization, data ingestion, data cleansing, ordered real-time data processing, or data migration. He's specialized in data.

​Scott Haines, Developer Relations Engineer, Buf

​Scott Haines is a seasoned software engineer specializing in massive distributed data systems and streaming technologies. Over the past decade, he has built and scaled data infrastructure at leading companies including Yahoo!, Twilio, Nike, and currently Buf. Scott is the author of books on Apache Spark and Delta Lake, and helps organizations successfully adopt open-source technologies through his teaching and consulting work. He is also proud to be a Databricks MVP.