Staff Software Developer in Test
2 months ago
- Experience: 5+ years in software development, including 3+ years in test automation for complex systems.
- Technical Skills: Strong in Python (preferred) or Java, with expertise in frameworks like PyTest, Selenium, and Playwright for UI, API, and E2E testing.
- Automation Solutions: Proven ability to design scalable, reliable test automation systems.
- CI/CD & Cloud: Skilled in optimizing pipelines (e.g., Jenkins, GitLab CI) with AWS and DevOps practices.
- Monitoring: Familiarity with tools like Prometheus and Grafana for tracking test/system performance.
- Quality Metrics: Experience improving test coverage, reducing flakiness, and enhancing execution times.
- Experimentation: Open to exploring new tools and methods for faster, better results.
- Leadership: Skilled at mentoring and driving cross-team adoption of QA best practices.
- Communication: Strong communication skills in the English language for collaborating with diverse teams.
- Nice to have: Familiarity with AI/ML in test automation.
At PandaDoc, engineering teams are divided into product teams, which focus on delivering new features, and the Platform Track, which provides the foundation that enables these teams to work efficiently. The Platform Track is responsible for managing infrastructure, automating workflows, and optimizing development environments to improve the developer experience, increase productivity, and ensure faster, higher-quality product delivery across the organization
About the Role:As a Staff SDET, you will define and execute company-wide test automation strategies to ensure scalability, reliability, and quality across all products. You will play a critical role in influencing system design, mentoring engineers, and driving initiatives that improve the efficiency of our development lifecycle. This is a high-impact role, working closely with leadership to ensure that our engineering practices set the standard for quality.
Our stack:- Service-oriented architecture, including legacy code and monolithic services (Django-based)
- Main stacks: Python (AsyncIO, Django) and Java (Spring Boot, Java 11, Gradle)
- Extensive use of AWS and Kubernetes for provisioning and deploying workloads
- Cross-service communication: NATS (migrating to gRPC), Kafka, Debezium for event-driven operations, RabbitMQ for Celery, and Temporal.io
- Monitoring and tracing: Grafana stack for monitoring, alerting, and distributed tracing (LGTM)
- Testing frameworks: PyTest, Selenium, Playwright, Appium
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