Staff Software Engineer - Data Platform

Okta Okta · Enterprise · Bangalore, India · SW Eng - Infrastructure-672

Okta is seeking a Staff Software Engineer for their Data Platform team. This role will focus on designing, building, and deploying scalable data-intensive platform components and infrastructure to support Okta's data analytics and ML initiatives, aiming to improve end-user security through data and machine learning. The role involves working with modern data technologies and distributed systems.

What you'd actually do

  1. Design, implement and own data-intensive, high-performance, scalable platform components
  2. Work with engineering teams, architects and cross functional partners on the development of projects, design, and implementation
  3. Conduct and participate in design reviews, code reviews, analysis, and performance tuning
  4. Coach and mentor engineers to help scale up the engineering organization
  5. Debug production issues across services and multiple levels of the stack

Skills

Required

  • 8+ years of experience in object-oriented language, preferably Java
  • Hands-on experience using a cloud-based distributed computing technologies
  • 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
  • Experience developing Kubernetes based services on AWS Stack

What the JD emphasized

  • high volume, low-latency, distributed data-platform services & data products
  • scale for years to come
  • design and own the building, deploying and optimizing the streaming infrastructure
  • make OKTA a leader in the use of data and machine learning to improve end-user security
  • sizable impact on the direction, design & implementation of the solutions