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Staff Software Engineering (Stream Processing- Identity Threat Protection)Okta • United States
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Staff Software Engineering (Stream Processing- Identity Threat Protection)

Okta
  • US
    United States
  • US
    United States
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About

Get to know Okta Okta is The World’s Identity Company. We free everyone to safely use any technology, anywhere, on any device or app. Our flexible and neutral products, Okta Platform and Auth0 Platform, provide secure access, authentication, and automation, placing identity at the core of business security and growth. At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box - we’re looking for lifelong learners and people who can make us better with their unique experiences. Join our team! We’re building a world where Identity belongs to you. The Identity Threat Protection Team Okta’s Identity Threat Protection (ITP) team is at the forefront of trust and security for the digital world. We build the platform services that protect our customers from attack and abuse. Our team focuses on securing the Okta Customer Identity Cloud, which enables the world’s largest brands to provide safe, seamless access for their users. At the heart of our defense is a real-time data platform that processes billions of events to detect threats. We are a team of Data Scientists, ML engineers, and Java developers building a next-generation security system that leverages Okta AI to continuously evaluate threats. Your work on our stream processing engine will be the foundation that powers our risk-based authentication policies and machine learning models. The Staff Software Engineer Opportunity We are seeking a Staff Software Engineer specializing in Stream Processing to lead the architecture and development of our core data ingestion and threat detection pipelines. You will be responsible for designing, building, and scaling the Flink-based systems that process massive volumes of security signals in real-time. This is a critical, high-impact role where you will solve complex security and distributed systems challenges at an immense scale. As a subject matter expert, you will set the technical vision for stream processing within the team, mentor other engineers, and ensure our data platform is robust, performant, and reliable. You will share our passion for elegant solutions and will join an engineering team that strongly believes in designing for scale, rigorous code reviews, and automated testing. What you’ll be doing
Own the architectural design, development, and delivery of our cloud-native, real-time stream processing platform, with a focus on Apache Flink.
Engineer data pipelines for large-scale data ingestion and feature engineering to power our machine learning models and complex rule-based systems.
Develop across the entire Okta stack, from core Java services to our microservice architecture
Lead the evaluation and implementation of new data technologies to solve complex security and ML challenges.
Mentor senior and junior engineers on distributed systems best practices and stream processing design patterns.
Evaluate and optimize for trade-offs between correctness, robustness, performance, and cost to ensure our platform operates effectively at scale.
Participate in on-call rotations to expeditiously unblock customers and make them successful
What you’ll bring to the role
8+ years of strong software development experience in an object-oriented language, with deep expertise in Java.
Demonstrated expertise in designing, building, and operating large-scale stream processing systems using frameworks like Flink or Storm; Flink experience is highly desired.
Proven experience with data ingestion at scale and building complex data pipelines.
Strong experience with cloud-native architecture and rolling out microservices at enterprise scale.
An excellent grasp of software engineering principles, scalability patterns, and security engineering.
Experience working with a variety of data stores including RDBMS, NoSQL, and time-series databases.
Experience working with Kafka streams at scal
And extra credit if you have experience in any of the following!
Experience with machine learning / Python and collaborating with Data Scientists.
Experience building anomaly detection or risk systems.
Experience in cloud security, identity, and/or authentication protocols.
#BB-1 Below is the annual base salary range for candidates located in California. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit:
. The annual base salary range for this position for candidates located in the San Francisco Bay area is between: $188,000—$282,000 USD What you can look forward to as a Full-Time Okta employee!
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Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta
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. Some roles may require travel to one of our office locations for in-person onboarding. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this
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