Black Duck Software, Inc. helps organizations build secure, high-quality software, minimizing risks while maximizing speed and productivity. Black Duck, a recognized pioneer in application security, provides SAST, SCA, and DAST solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open-source components, and application behavior. With a combination of industry-leading tools, services, and expertise, only Black Duck helps organizations maximize security and quality in DevSecOps and throughout the software development life cycle.
Key Responsibilities:
- Deploy and set up test instances and PostgreSQL OR Any databases on-prem on Linux and in the cloud in AWS OR GCP leveraging Docker, Kubernetes, and Jenkins and working heavily in the command-line.
- Troubleshoot deployment issues, test issues, and product issues.
- Develop performance tests using tools such as LoadRunner, DevWeb (JavaScript), Apache Benchmark (ab), and Cypress, and custom tools and scripts written in Python, Perl, Bash, and SQL.
- Monitor, analyze, and use whatever it takes to diagnose issues and bottlenecks and gain insights, including but not limited to: test results, Jenkins logs, application logs, PostgreSQL logs, Docker, Kubernetes, NetData, Prometheus, Grafana, New Relic, Datadog, AWS or GCP cloud monitoring, RabbitMQ, custom PostgreSQL OR DBA queries.
- File and track product issues in Jira with sufficient details for developers to reproduce and fix the issues.
- Work closely with engineering teams to investigate and mitigate problems found in testing.
- Improve automation so that more time can be spent analyzing measurements rather than just obtaining them.
- Take ownership of tasks, demonstrate initiative, communicate proactively, learn from mistakes, and continuously improve.
Key Requirements (Must):
- Enjoy performance engineering, are good at it, and have 6+ years of dedicated experience doing it, preferably with complex, containerized, distributed products in the cloud.
- Strong experience with:
o Linux
o Docker and Kubernetes
o GCP and/or AWS
o LoadRunner, JMeter, or other performance testing tools
o Scripting, such as with Bash, Perl, or Python
o Diagnosing bottlenecks in PostgreSQL queries or other relational database queries
o Performance monitoring tools such as New Relic, Prometheus, Grafana, or Datadog
