Jaebin Yoon

I lead a talented team responsible for building and managing batch and streaming data connectors for diverse data stores, leveraging technologies like Flink, Spark, and Kafka to enable the reliable movement of large-scale data across the Netflix ecosystem.

• Worked on batch and streaming data connectors for CDC data movement solutions across various data stores. • Led an effort to support large scale Cassandra CDC events to Iceberg, optimizing data transfer efficiency. • Collaborated with cross-functional teams at Netflix to ensure seamless data movement processes.

Netflix is a data-driven company, handling trillions of events per day to answer many application and business related questions. At the center of providing scalable solutions to these challenges is the Netflix Real Time Data Infrastructure team. Our team is responsible for building Messaging as a Service (Kafka) and Stream Processing as a Service (Flink) to collect, transport, aggregate, process and visualize various events. Other engineering teams at Netflix use the platform and build realtime data processing applications and insights on the platform. Within the team, I've been responsible for architecting/building/operating the data transport layer with Kafka clusters providing them as a service to the rest of Netflix teams.

- Designed and implemented scalable, robust realtime/batch data pipeline with Apache Beam (Dataflow), PubSub, BigTable, BigQuery in Google Cloud Environment (Scala, Python, Go) - Replaced and re-architected ad-hoc python apps with MongoDB with the reliable and flexible data pipeline using the streaming processing technology and scalable storage (BigTable, BigQuery) to process billions of events - Built the system infrastructure for a relevant search, user segmentation, and product recommendation

- Led the next generation ad platform initiative and proposed initial architecture - Led the next generation data architecture discussions and proposed the one covering various aspects of data architecture including : * evolutionary data ingestion for realtime/batch pipeline * meta data management * business continuity plan for big data * hybrid data processing on both cloud and on-premises * Data governance

- Spearheaded adoption of Druid as new analytics platform to provide multi-dimensional queries/reports over huge event data (more than 20B ad requests, hundreds of billions of events per day) - Built realtime data pipeline with Kafka, Spark Streaming, Druid - Implemented Data analytics dashboard with AngularJS - Implemented Spark Streaming stateful event joins (with Scala) - Built server-side header bidding with Kubernetes, Google Pub/Sub, BigQuery on Google Cloud Platform (with Elixir) - Architected Ad-Quality pipeline with Kafka - Worked on/Debugged Apache Storm for real time Ad-Quality analytics - Built Mobile SSP reporting pipeline (with python)

- Web-app backend development in GoPayment team using Groovy/Grails, Java - Web-app frontend development with AngularJS and LESS (CSS) (Full stack development) - iOS development in GoPayment team (Onboarding process) - Javascript Test Environment with Grunt, Karma, Nodejs - Data mining with Hadoop ecosystem - Data visualization in web browsers with javascript (D3)

- Worked within a small group of engineers in a startup environment wearing various hats (developer, product owner, sys admin, etc) - Developed web and mobile applications for instant deals, location POI search using application stack of Django, Nginx, Gunicorn, Apache, Haproxy, PostgreSQL, MongoDB, RabbitMQ in AWS clouding environment - Designed and implemented back-end RESTful APIs for the system and designed database models for various system components

- Involved in architecture, design and implementation of the flagship product, Spirent TestCenter (network protocol testing equipment). - Member of the architecture team developing prototypes for new technologies in rapid development process. Worked as a technical lead within firmware team. - Successfully delivered key components of products such as messaging modules in C, C++ and Python, Linux kernel porting for custom boards, high performance Linux network drivers and those were proven to be reliable and efficient. - Provided development platforms for other developers in challenging environment where various cross compile/packaging platforms coexist. Created and introduced new tools and technologies to others. - Successfully delivered industry first multiple OS solution on multi-core CPU to reduce cost and maximize core usage.

I implemented many network protocols for Smartbit TeraMetrics (Network test environment) such as IGMP v1,v2,v3, arp, ipv6 neighbor discovery, router discovery, MLD, PPP, STREAM based protocols, etc. The challenging part was that you have to implement protocols to test other protocol implementations on various network devices, which requires scalable and precise implementation of protocols. I was responsible for linux kernel development and maintenance. I tried to enhance network performance in linux environment and learned many aspects of network performance during that time.

I had lots of fun at USC. I enjoyed Operating System and compiler courses. Their courses are balanced between theory and practice. I'm really grateful for what it taught me there.