SDET – Backend QA Platform Engineer
New
Based in United StatesFull-TimeSenior
Salary86,320 - 160,308 USD per year
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Job Details
- Experience
- 6+ years
- Required Skills
- AWSPythonSQLFlaskNosqlSeleniumCI/CDLinuxDatadog
Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
- 6+ years of backend engineering or QA automation experience in complex software environments.
- Strong programming experience in Python, with deep expertise in backend development and test automation.
- Hands-on experience building automated testing frameworks using Selenium and pytest.
- Solid understanding of SQL and relational databases, along with familiarity with NoSQL systems.
- Experience developing and integrating backend systems using Python-based frameworks such as Flask.
- Familiarity with frontend fundamentals including JavaScript, HTML, and CSS for testing and integration purposes.
- Experience working with version control systems and integrating code into large, existing codebases.
- Exposure to cloud environments (especially AWS) and monitoring tools such as Datadog or AWS Inspector.
- Strong analytical thinking, problem-solving ability, and attention to detail in complex systems.
- Excellent communication and documentation skills with the ability to collaborate across engineering teams.
- Familiarity with Linux environments, JIRA, and CI/CD workflows is highly valued.
Responsibilities
- Design, develop, and maintain scalable backend QA systems and automated testing frameworks supporting IoT, machine learning, and data analytics platforms.
- Build and execute automated test suites using tools such as Selenium and pytest to ensure system reliability and performance.
- Develop backend services and test infrastructure using Python and frameworks such as Flask, ensuring robustness in 24/7 production environments.
- Integrate testing systems with relational and NoSQL databases, APIs, and existing data storage solutions.
- Create dashboards, reports, and quality metrics to monitor system health, test coverage, and regression results.
- Collaborate with engineering teams to embed automated testing into CI/CD pipelines and software development workflows.
- Identify QA process gaps and drive continuous improvement in testing strategies, tools, and best practices.
- Support backend development efforts for production systems when needed, ensuring seamless integration between QA and engineering.
- Implement monitoring and diagnostic solutions using tools such as Datadog or similar observability platforms.
- Ensure test systems are scalable, maintainable, and aligned with modern cloud and data engineering standards.
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