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Elastic is hiring a

Software Engineer- Data Ingestion- For Elastic- Great Work/Life Balance

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Job Description

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Logstash is data processing platform and an important component of the Elastic Stack. People choose Logstash for its simplicity and extensibility. Over the last few years, Logstash has evolved to become a powerful server-side platform responsible for ingesting and transforming terabytes of data into Elasticsearch from many data sources.

The Logstash team is responsible for developing the core data processing infrastructure and its thriving integrations. As Logstash matures into being a ubiquitous data ingestion pipeline, our team is building new features to make it faster, easier, and more reliable, to drive our next wave of adoption. You'll work with a geographically diverse, distributed and fun loving team. At Elastic we have a flexible, family-friendly work schedule. We make great software, love autonomy and collaboration, and most importantly, love our users.

What would I do?

  • You will Integrate and connect new data sources into the Elastic Stack.
  • Add new features for cloud based services like Kinesis, Google PubSub, Kafka, HDFS to broaden the reach of Logstash plugins.
  • Write code in Java and JRuby.
  • Craft end-to-end modules making it easy for users to connect and visualize data within minutes. You will collaborate with the Elasticsearch and the Kibana teams to build dashboards, define data schema, new transformation and processors, etc.
  • Our environment is highly collaborative; you will use tools like Zoom, Slack, and Github heavily. You will work with other development teams from UI, Cloud, Elasticsearch, support engineers, and solution architects regularly as you develop new features.
  • Speak at conferences, meetups, and internal events to engage with our users.

What do I need?

  • You have 5-7 years experience in a hands-on programming role.
  • Experience in Java is a huge plus, but not required. You should be open to programming in Java and some Ruby.
  • Experience working with data sources such as Elasticsearch, Kafka, Kinesis, Redis, DynamoDB.
  • You are curious and open to learning multiple technologies and APIs for connecting various services to the Elastic Stack.