Dubbed an "open-source unicorn" by Forbes, Confluent is the fastest-growing enterprise subscription company our investors have ever seen. And how are we growing so fast? By pioneering a new technology category with an event streaming platform, which enables companies to leverage their data as a continually updating stream of events, not as static snapshots. This innovation has led Sequoia Capital, Benchmark, and Index Ventures to recently invest a combined $125 million in our Series D financing. Our product has been adopted by Fortune 100 customers across all industries, and we're being led by the best in the space-our founders were the original creators of Apache Kafka®. We're looking for talented and amazing team players who want to accelerate our growth, while doing some of the best work in their career. Join us as we build the next transformative technology platform!
About the Role:
We are looking for an experienced software engineer to work on high impact security aspects of the Confluent Platform. Key challenges and opportunities here include collaborating with multiple engineering teams, contributing to designing and implementing mission critical features!
Who You Are:
* Smart, humble, and empathetic * Have a strong sense of teamwork and put team's and company's interests first * Driven and excited about challenges of a fast-paced, innovative software startup environment
* Collaborate with various Confluent Engineering groups to design, implement, and maintain platform security features
What We're Looking For:
* 5+ Years Proficiency in Java Experience with concepts of distributed systems and big data such as - Hadoop, Spark, Kafka, Big Table, HBase etc * A self starter with the ability to work effectively in teams with excellent spoken / written communication * Interest in Software Security
What Gives You An Edge:
* Experience in one of the following areas: Kerberos, LDAP, SSO, TLS * Experience working with Docker or Kubernetes * Experience working with AWS, Azure, GCP * Experience working with scanning tools
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