Join Okta as a Staff Software Engineer to design and build scalable data platform components for high-volume analytics and machine learning.
Posted by employer 3 months ago
First seen on Joblaze 3 months ago
Last verified on the company career page 1 day ago
Not disclosed in this posting: compensation, visa sponsorship.
Joblaze summary
In the role of Staff Software Engineer for the Data Platform at Okta, the individual will focus on designing and implementing high-performance, scalable data services that support analytics and machine learning initiatives. Proficiency in object-oriented programming, particularly Java, along with experience in cloud-based distributed systems like Kinesis and Snowflake, is essential. This position is ideal for seasoned engineers with a strong background in building and optimizing complex data infrastructures. The team is characterized by its fast-paced, innovative environment, emphasizing ownership and collaboration.
Quick facts
- Is the Principal Software Engineer in Test role remote?
- It's hybrid — Okta expects some on-site time in Bengaluru, India.
- How much experience is required?
- At least 8 years of relevant experience for this Principal Software Engineer in Test role.
- Where is the role based?
- Okta is hiring for this position in Bengaluru, India.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Beam, Flink, Hadoop, Java, Kafka, Kinesis.
- What seniority level is this role?
- Okta targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Principal Software Engineer in Test role at Okta.
From the original posting
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Job Duties and Responsibilities:
- Own and deliver complex, cross-team quality initiatives end-to-end — from ambiguous problem definition through architecture, implementation, and production rollout with minimal oversight
- Lead technical design discussions and drive stakeholder alignment on test strategy, architecture, and quality standards across engineering, product, and design
- Generate original solutions to ambiguous or previously unsolved quality problems; use sound engineering judgment when there is no obvious answer
- Anticipate, communicate, and manage quality and release risk across team boundaries; make prioritization trade-offs in partnership with engineering leadership
- Champion CI/CD, observability, monitoring/alerting, and production-hygiene practices, and drive their adoption beyond your own team
- Guide new and existing engineers on execution of sub-tasks within larger quality initiatives; raise the bar on code review standards for reliability, performance, security, and maintainability
- Partner with Engineering, Product, Design, Support, and Field/CSM teams to identify recurring customer issues and drive systemic product and process improvements
- Respond to and help resolve critical production issues/customer escalations during on-call rotation, driving root-cause analysis
- Mentor engineers, contribute to hiring and interviewing, and help improve engineering culture across the team and adjacent teams
- Drive adoption of AI powered testing capabilities — such as AI-assisted test case/script generation, self-healing test automation, and AI-driven test coverage or anomaly/log analysis — to improve quality engineering efficiency and coverage across teams
- Evaluate emerging AI tooling and agentic testing frameworks, and lead pilots to integrate them into existing automation and CI/CD pipelines
Minimum REQUIRED Knowledge, Skills, and Abilities:
- 8+ years of quality/test engineering experience with deep, hands-on test automation expertise across API, end-to-end, and performance/scale testing
- 8+ years of experience building and scaling automation frameworks using Java (or equivalent object-oriented language), including UI and/or API testing tooling
- 5+ years of experience designing and executing performance, load, and reliability testing (e.g., JMeter, Gatling) and using results to influence engineering decisions
- 5+ years of experience with observability and diagnostic tooling (Splunk, Datadog, Grafana), SQL, and Unix/Linux systems
- Demonstrated ability to independently own and deliver cross-team, ambiguous technical projects without oversight, including planning, scoping, and production readiness (scalability, monitoring, alerting, resource efficiency)
- Proven track record of influencing technical direction and driving alignment across multiple teams and stakeholders (engineering, product, design)
- Strong written and verbal communication skills; experience leading technical design discussions and building stakeholder buy-in
- Experience mentoring engineers and contributing to team hiring/interviewing processes
- Hands-on experience applying AI/ML tools to quality engineering — e.g., LLM-based test/code generation, AI coding assistants (Copilot, Cursor, Claude Code), self-healing test frameworks, or AI-driven anomaly/log analysis
- Ability to quickly learn new technologies, evaluate trade-offs, and provide technical direction to others
Education and Training:
B.S. in Computer Science or related field, or equivalent practical experience. Advanced degree a plus.
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