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Mid-level experience, metro location, and a visible engineering role increase applicant density.
Performance testing, cloud, Kubernetes, and DB tuning skills transfer across software firms but remain somewhat domain-specific.
Multiple mandatory tools and explicit 3+ years dedicated performance-engineering requirement increase filter strictness.
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Deploy and configure performance test environments using databases on Linux and cloud platforms (AWS/GCP) leveraging Docker, Kubernetes, and Jenkins.
Develop and execute performance tests with tools like LoadRunner, Apache Benchmark, Cypress, and custom scripts in Python, Perl, Bash, and SQL.
Monitor and analyze system and application performance using logs and monitoring tools (New Relic, Prometheus, Grafana, Datadog) to identify bottlenecks and issues.
Minimum 3 years of dedicated performance engineering experience, preferably with containerized, distributed cloud products.
Strong proficiency with Linux, Docker, Kubernetes, and either AWS or GCP cloud platforms.
Experience with performance testing tools such as LoadRunner or JMeter and scripting in Bash, Perl, or Python.
Ability to diagnose SQL query performance issues in PostgreSQL or other relational databases and use monitoring tools like New Relic, Prometheus, Grafana, or Datadog.
Experienced in managing complex, containerized applications deployed in cloud environments with strong command-line skills.
Skilled in integrating performance testing and monitoring within CI/CD pipelines (e.g., Jenkins).
Analytical approach to diagnosing and resolving performance bottlenecks across distributed systems and databases.