San Francisco 2022
Our program committee take responsibility for planning and shaping the program of Flink Forward. They make sure to rate talks in different dimensions to create a balanced program including deeply technical talks and high-level use cases. Diversity is also a crucial aspect for the program committee - they strive to improve and support the presence of underrepresented groups at the conference.
Co-Founder at Immerok
Program Committee Chair
Timo Walther is a long-term committer and PMC member of the Apache Flink project. He studied Computer Science at TU Berlin. Alongside his studies, he participated in the Database Systems and Information Management Group there and worked at IBM Germany. Timo worked as a software engineer and lead of the SQL team at Ververica. In Flink, he is working on various topics in the Table & SQL ecosystem.
Principal Software Engineer at Splunk
Program Committee Member
Tzu-Li (Gordon) Tai is an Apache Flink Committer and PMC Member, currently employed at Splunk where he works with the Streaming Compute team on a platform for managing and autoscaling streaming pipelines. Prior to that, he was at Ververica, where he had worked on various components in Apache Flink and the Stateful Functions subproject. He was introduced into the fascinating world of data streaming systems early in his career building real-time data pipelines, and has remained passionate about building distributed systems for data intensive applications ever since
Engineering Manager (Stream Processing Engines) at Netflix
Program Committee Member
Calvin Cheung is the Engineering Manager for the Stream Processing Engines team at Netflix. His team provides a fully managed platform to build and operate Flink jobs used engineers and data scientists alike. Throughout his career at Twitter, Uber, and Netflix, he has been an operator and builder of large scale data systems. An active committer on Netflix’s very own open source real time data platform — Mantis. Its focus on high availability and low latency is a perfect complement to Flink.
Principal Data Engineer previously at Epic Games
Program Committee Member
Ricky Saltzer was previously a Principal Data Engineer at Epic Games where he primarily focused on real-time data processing and large scale distributed systems. Previously, he worked as a Senior Data Engineer at Cloudera where he managed/leveraged the internal Hadoop cluster. In addition, Ricky is a committer on the Apache NiFi project and previously delivered the keynote at Flink Forward 2020 on "Real-time Metrics at Fortnite Scale".
Managing Director & Tech Pro (Data Lake Engineering) at Goldman Sachs
Program Committee Member
Regina Chan is a Managing Director and Tech Fellow within Data Lake Engineering at Goldman Sachs where she drives data strategy through building platforms. She is a founding member of the team that built the Data Lake, the firm’s largest data platform and led it through its latest implementation using Flink. Outside of work, she likes to geek out in everything she does, whether it is cooking, rock climbing, or coding or anything else she’s currently learning.
Engineering Manager at Apple
Program Committee Member
Enrico is the Engineering Manager of the Stream Data Platform team at Apple. This team runs a massive scale Flink powered platform to support Apple’s stream data processing. Enrico loves designing reliable large scale software solutions for stream processing that are provided as a self-serve platform to application developers. Prior to Apple, Enrico has led the teams that built and maintained the Kafka and Flink deployments, powering the Data Pipeline at Yelp.
Senior Software Engineer at Disney Streaming
Program Committee Member
Nick Burkard is a Senior Software Engineer at Disney Streaming where he builds real-time, event-driven distributed systems. He is an avid fan of Scala and functional programming; advocating for their use wherever possible. He is also active in open-source, having contributed to the Apache Flink project and created a library for managing infrastructure in AWS as idiomatic Scala code.
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