We are looking for experienced Software Engineers who can help design and own the building, deploying and optimizing the streaming infrastructure. This project has a directive from engineering leadership to make OKTA a leader in the use of data and machine learning to improve end-user security and to expand that core-competency across the rest of engineering. You will have a sizable impact on the direction, design & implementation of the solutions to these problems.
Job Duties and Responsibilities
Design, implement and own data-intensive, high-performance, scalable platform components
Work with engineering teams, architects and cross functional partners on the development of projects, design, and implementation
Conduct and participate in design reviews, code reviews, analysis, and performance tuning
Coach and mentor engineers to help scale up the engineering organization
Debug production issues across services and multiple levels of the stack
Participate in the on-call rotation, and incident management
Required Knowledge, Skills, and Abilities
5+ years of industry experience
2+ years of experience in object-oriented language, preferably Java
Experience developing Kubernetes based services
Hands-on experience using a cloud-based distributed computing technologies including
Messaging systems such as Kinesis, Kafka
Data processing systems like Flink, Spark, Beam
Storage & Compute systems such as Snowflake, Databricks, Hadoop
Coordinators and schedulers like the ones in Kubernetes, Hadoop, Mesos
Experience in developing and tuning highly scalable distributed systems
Excellent grasp of software engineering principles
Solid understanding of multithreading, garbage collection and memory management
Experience with reliability engineering specifically in areas such as data quality, data observability and incident management
Nice to have
Maintained security, encryption, identity management, or authentication infrastructure
Leveraged major public cloud providers to build mission-critical, high volume services
Hands-on experience in developing Data Integration applications for large scale (petabyte scale) environments with experience in both batch and online systems.
Contributed to the development of distributed systems or used one or more at high volume or criticality such as Kafka or Hadoop
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