Speaker: Gwen Shapira

Principal Data Architect @Confluent, PMC Member @Kafka, & Committer Apache Sqoop

Gwen is a principal data architect at Confluent helping customers achieve success with their Apache Kafka implementation. She has 15 years of experience working with code and customers to build scalable data architectures, integrating microservices, relational and big data technologies. She currently specializes in building real-time reliable data processing pipelines using Apache Kafka. Gwen is an author of “Kafka - the Definitive Guide”, "Hadoop Application Architectures", and a frequent presenter at industry conferences. Gwen is also a committer on the Apache Kafka and Apache Sqoop projects. When Gwen isn't coding or building data pipelines, you can find her pedaling on her bike exploring the roads and trails of California, and beyond.

Find Gwen Shapira at

Proposed Tracks

  • Real-World Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.

  • Deep Learning Applications & Practices

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe across machine translation, computer vision.

  • AI Meets the Physical World

    The track where AI touches the physical world, think drones, ROS, NVidea, TPU and more.

  • Data Architectures You've Always Wondered About

    How did they do that? Real-time predictive pipelines at places like Uber, Self-Driving Cars at Google, Robotic Warehouses from Ocado in the UK, are all possible examples.

  • Applied ML for Software

    Practical machine learning inside the data centers and on software engineering teams.

  • Time Series Patterns & Practices

    Stocks, ad tech/real-time bidding, and anomaly detection. Patterns and practices for more effective Time Series work.