Define, develop and perform performance/scalability benchmarks on Splunk observability cloud and Cloud products
Efficiently working with various profiling tools to identify performance and concurrency bottleneck, propose and implement optimizations to improve the Splunk products and Splunk observability cloud.
Implement and improve sizing and capacity calculators for key Splunk observability cloud applications on the cloud.
Who You Are What Makes You Qualified :
8 - 12 years of experience 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, strace, tcpdump, netstat, ext4slower, opensnoop
Passionate about finding performance bottlenecks and optimize code
Experienced in solving problems of load, scale, and optimizations of sophisticated large-scale deployments
Demonstrated ability in SaaS, Microservice, Cloud Native software companies and projects
Expert in scripting languages such as Shell, Python and compiled languages (C/C++)
Proficient in Linux, Docker, AWS, GIT, Artifactory in terms of both tools and systems administration
Experience in leading and growing a team of junior engineers
Ability to coordinate activities such as sprint planning, design reviews, code review, and providing updates to engineering manager
Extended Qualifications
Experience with Splunk observability cloud enterprise software capacity planning a huge plus
Experience with big data (Hadoop, Spark) a huge plus
Experience with data science and ML a plus
Experience with GPU a plus
Requirements
Strong fundamentals in software engineering: data structures and algorithms
Coding proficiency in one or more of the following languages with the ability to quickly learn new languages: Python, Java, Go, Python, C++
Experience in working on distributed systems like databases, distributed file systems, distributed concurrency control
Strong debugging and troubleshooting skills including the use of associated tools
Experience with developing CI/CD systems with Gitlab, test automation frameworks,
Ability to document your work for the benefit of the team
Knowledge of REST, grpc or similar communication paradigms
Knowledge of public cloud services such as AWS, GCP, Azure
Operational excellence: You think beyond feature delivery into how your code is serving customers in production
Familiarity with Kafka and data streams for data processing and testing purposes.
Expertise in software quality engineering principles and practices, including test planning, test case design, and quality assurance methodologies.
Proven ability to diagnose escalations and production issues and work on effective solutions.
Strong analytical skills to identify and address test gaps and improve test coverage.
Bachelors degree or higher in Computer Science, or equivalent practical experience
8 -12 years of related experience with a Bachelors degree or Masters degree; or equivalent experience
