Software Engineer – Performance
| Company | Splunk |
|---|---|
| Location | Texas, USA, Colorado, USA |
| Salary | $117120 – $201300 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior |
Requirements
- Passionate about finding software performance bottlenecks and optimize product code
- Fluent in any of Python (C++ or Go would be a huge plus)
- Knows the principles of distributed computing systems
- Comfortable with Linux, Docker, AWS, GIT, Artifactory in terms of both tools and systems administration
- BS degree in Computer Science, similar technical field of study or equivalent practical experience
- minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or a PhD without experience; or equivalent work experience.
- mentoring/leading teams
- Experience in SaaS, Microservice, Cloud Native software companies and projects
Responsibilities
- Define, design and implement performance / scalability / reliability (PSR) benchmarks on Splunk Enterprise and Cloud products
- Heavily contribute in the design and implementation of self-service tools for Splunk developers to find performance bottlenecks by themselves
- Efficiently working with various profiling tools to identify performance and concurrency bottleneck, propose and implement optimizations to improve the Splunk products
- Implement and improve sizing and capacity calculators for premium Splunk applications on the cloud
- Demonstrated ability in Performance Engineering and Benchmarking
- Skilled in both the art and science of benchmark creation and measurement and modeling of system behavior under load
- Ability to find root cause of performance bottlenecks with profiling tools: flamegraphs, pprof, pstack, qmlprofiler, perf, nmon
- Get certified in Splunk Fundamentals
Preferred Qualifications
- Experience in solving problems of load, scale, and optimizations of sophisticated large-scale deployments
- Experience with enterprise software capacity planning
- Experience with data science and ML
- Experience with GPU