Amazon Kinesis Data Analytics(KDA) team is looking for engineers who are passionate to build distributed stream processing engines. We are looking for builders who are enthusiastic about data streaming and excited about contributing to open source.
Real-time data processing from a stream needs substantial investments from customers in writing the application and maintaining the necessary infrastructure. KDA service provides customers with fully managed stream processing platform where customers can develop their applications using SQL or Java. With the service all that customers need to do is provide the application code that needs to be run containing the business logic to process the stream and service takes care of providing building blocks/abstractions such as processing windows, execution semantics, checkpoints and infrastructure capabilities such as elasticity, fail-over etc. eliminating complexity of stream processing.
As a member of KDA team you will be working on making improvements to the stream processing engine, Apache Flink to make KDA service defacto service to run stream processing application. Upstream compatibility is a core tenet of KDA service and your changes to improve the engine will be contributed back to open source. As a member of the KDA service you will be working on adding new stream processing operators, improving efficiency and availability of the engine and push the envelope of stream processing.
The ideal candidate has experience working on large-scale systems, enjoys solving complex software problems, and possesses analytical, design and problem-solving skills. While not necessary having an in-depth understanding of data processing technologies such as Apache Flink, Apache Spark, Apache Storm, Hadoop frameworks is a plus. Your responsibilities will include collaborating with other engineers to build a large scale AWS service, and work with senior leaders to define your team's roadmap, including identifying design and code changes needed in the underlying open source platforms.
Come join us to make stream processing main stream for our customers.
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