17th Meetup: Apache Beam Pipelines At Cash App: An Introduction

At Cash App, Apache Beam is one of several tools for creating data pipelines for leveraging distributed computing for transforming data for ML applications. Cash App uses both the Java and Python SDK for developing pipelines. In this session, I will highlight how we use the Apache Beam python SDK to create data components used for both batch and streaming pipelines. I will also highlight our approach to leveraging several best practices for machine learning as we design, build, test and deploy our data pipelines using cloud services like Google DataFlow.

Bio
Kyle De Freitas is a Senior Machine Learning Engineer at Block, working on AI solutions for identity verification in Cash App. Kyle leads a team of ML practitioners across Canada and the US, working on using internal and external data sources to prevent bad actors from getting in and creating opportunities for traditionally disadvantaged users in Cash App.

Kyle has several years’ experience leading various software projects in the Caribbean. In addition, he has almost ten years of experience mentoring and teaching young software developers. He has contributed to several ICT initiatives in the Caribbean which benefited disadvantaged populations in the Caribbean in Agriculture, Fisheries and Education. In addition, Kyle has participated in several local and regional ICT capacity-building initiatives with agencies such as NIHERST, Caribbean Telecommunications Union, The World Bank, The Caribbean Open Institute, the International Development Research Centre and the Caribbean ICT Research Programme