About the role
As a Software Development Engineer in Test (SDET) - Data Cloud, you will work as part of a high-performing engineering team responsible for validating cloud-native services that support medical devices, mobile applications, partner integrations, and data platforms. You will contribute to test automation, system validation, and quality engineering practices while developing strong foundations in cloud systems, data pipelines, and AI-enabled applications.
Responsibilities:
- Develop and execute functional and integration test suites for cloud-based services.
- Contribute to test automation frameworks and expand automated test coverage.
- Partner with development teams to identify and resolve defects.
- Participate in API, microservices, and integration testing.
- Support validation of distributed and cloud-based systems.
- Assist with debugging, root cause analysis, and release validation.
- Participate in Agile development and testing processes.
AI and Modern Engineering:
- Develop familiarity with AI-Driven Development Lifecycle (AI-DLC).
- Contribute to validation of AI-powered features (e. g., AWS Bedrock).
- Build awareness of agent-based systems and MCP integrations.
- Use AI-assisted tools to improve test creation and productivity.
Data and Streaming Quality:
- Contribute to testing systems processing telemetry and real-time data.
- Validate data accuracy, completeness, and consistency.
- Learn event-driven and streaming system testing (e. g., Kafka).
Technical Expectations:
- Understanding of software testing fundamentals.
- Programming skills in Java or Python.
- Familiarity with APIs, Git, and basic CI/CD.
- Interest in cloud systems (AWS preferred) and distributed systems.
Requirements:
- Bachelor's degree in Computer Science or related field.
- 3-5 years of testing experience.
- Relevant experience including internships or academic projects.
- Strong problem-solving and communication skills.
Success Criteria:
- Delivers high-quality automated and manual test coverage.
- Demonstrates growth in cloud, data, and AI testing fundamentals.
- Contributes to reliable and scalable system validation.