QA Engineer

Job Description: Quality Engineer

We are seeking an experienced Quality Engineer to join our team and ensure the quality and reliability of our federated data mesh platform. As a Quality Engineer you will play a crucial role in designing and implementing quality assurance processes and practices as well as performing rigorous testing and analysis to ensure the platform meets high standards of performance security and scalability.

Responsibilities:

Develop and implement quality assurance processes: Design and implement quality assurance processes and methodologies for the federated data mesh platform ensuring that best practices are followed throughout the development lifecycle.

Perform testing and analysis: Conduct thorough testing of the platform including functional integration regression performance and security testing to identify and address any defects or issues ensuring a robust and reliable platform.

Develop test plans and test cases: Create comprehensive test plans and test cases based on requirements and specifications covering all aspects of the federated data mesh platform and execute them to validate the platforms functionality and performance.

Automate testing processes: Develop and maintain automated testing frameworks and tools to streamline the testing process improve efficiency and ensure consistent and repeatable results.

Collaborate with crossfunctional teams: Work closely with developers architects and product managers to understand requirements provide feedback on design and functionality and ensure that quality considerations are addressed throughout the development process.

Monitor and track issues: Use bug tracking and project management tools to track and manage issues ensuring that defects are properly logged prioritized and resolved in a timely manner.

Perform security and vulnerability assessments: Conduct security testing and vulnerability assessments to identify potential risks and vulnerabilities within the federated data mesh platform and collaborate with the security team to implement appropriate measures for mitigation.

Stay updated with industry trends: Keep abreast of the latest advancements in quality assurance practices testing methodologies and emerging technologies and apply that knowledge to drive continuous improvement and innovation within the federated data mesh platform.



Requirements:

Proven experience as a Quality Engineer: Minimum 3 years of experience in quality assurance and testing preferably in a data engineering or platform development environment.

Strong knowledge of quality assurance processes: Solid understanding of quality assurance methodologies best practices and tools with experience in designing and implementing quality assurance processes for complex software platforms.

Proficiency in testing techniques: Experience in functional integration regression and performance testing as well as familiarity with test automation frameworks and tools (e.g. Selenium JUnit Postman DQ Great Expectations etc).

Data engineering knowledge: Understanding of data engineering concepts including data governance data integration and data processing to effectively test and ensure the quality of the federated data mesh platform.

Security testing experience: Familiarity with security testing methodologies and tools such as vulnerability scanning penetration testing and secure coding practices to identify and mitigate potential security risks within the platform.

Analytical and problemsolving skills: Strong analytical and problemsolving abilities to identify troubleshoot and resolve complex technical issues and to provide valuable insights and recommendations for platform improvements.

Excellent communication and collaboration skills: Effective verbal and written communication skills with the ability to work collaboratively with crossfunctional teams and stakeholders and to clearly articulate complex technical concepts and issues.

Strong attention to detail: Meticulous attention to detail to ensure accuracy and completeness in testing documentation and issue tracking.

Continuous learning mindset: Eagerness to stay updated with the latest trends and advancements in quality assurance data engineering and emerging technologies and a commitment to continuous learning and improvement.