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Modern Data Engineering

In the "old" days, data engineering was all about getting data from a transactional data store to a data warehouse, whereby it enabled business analysts to create reports and gain insights. In this track we’ll explore the ways in which data engineering has changed in the last few years and has become key to the success of products and companies - new requirements breed new solutions. Data & data engineering are used to power mission critical production applications, create powerful network effects, predict user behavior and drive cutting-edge AI. Come to this track to learn about recent advances in the theory and practice of data engineering.


Sid Anand

Chief Architect @Datazoom, PMC/Committer @Apache Airflow, Co-chair @QCon I currently serve as the Chief Architect for Datazoom. Prior to joining Datazoom, I served as PayPal's Chief Data Engineer, focusing on ways to realize the value of data. Prior to joining PayPal, I held several positions including Agari's Data Architect, a Technical Lead in Search @ LinkedIn, Netflix’s Cloud Data Architect, Etsy’s VP of Engineering, and several technical roles at eBay. I earned my BS and MS degrees in CS from Cornell University, where I focused on Distributed Systems. Outside of work, I'm a maintainer/committer on Apache Airflow and I co-chair QCon, a family of popular practitioner-driven technical conferences, and Data Council, a global Data & AI conference. I also offer technical advisory services to startups and serve on the boards of a few companies. Find Sid Anand at:

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3 weeks of live software engineering content designed around your schedule.

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