Data engineers around the world have embraced python as the language of choice for designing and developing data engineering pipelines. For streaming data, python DSLs serve the purpose of writing complex business logic in a fluent, readable and efficient way. Apache Flink Table API python transforms enable data streaming engineers to write sophisticated stream transforms such as tumbling, hopping windows and group by key aggregations with pure pythonic fluent DSLs. Join this session to learn the beauty and ease of use of writing python Table API transformations on streaming data with Kafka as the source. This session would also show a live demo of writing python Table API aggregations on streaming data with Kafka. The audience would come out of this session armed with the knowledge of writing complex streaming data transformations using their popular language of choice, python and understand how to construct streaming data pipelines using Apache Flink Table API.