Knowledge Informatics QA Engineer

Baylor Genetics

About The Position

As a QA Engineer for Knowledge Informatics, you will be responsible for ensuring the quality, accuracy, and integrity of data and information systems within the knowledge management and informatics environment. This role involves performing comprehensive testing of data-driven applications, working with data integration systems, and collaborating with cross-functional teams to ensure that knowledge systems meet both functional and regulatory requirements. You will help ensure the delivery of high-quality products that drive organizational efficiency and enhance decision-making.

Requirements

3+ years of experience in Quality Assurance engineering, with a focus on data-driven applications and informatics systems.
Hands-on experience with QA tools and frameworks for testing applications, especially in knowledge management or informatics domain.
Experience with data validation, data integration testing, and ensuring data quality.
Familiarity with regulatory requirements and compliance standards related to data management (e.g., HIPAA, GDPR).
Strong knowledge of manual and automated testing techniques and tools (e.g., Selenium, JUnit, TestNG).
Proficient in scripting languages such as Python, Java, or SQL for test automation and data manipulation.
Experience with version control systems such as Git.
Strong analytical and problem-solving skills, with attention to detail in identifying and addressing issues.
Familiarity with CI/CD pipeline tools and processes.
Excellent communication skills and the ability to collaborate with cross-functional teams to drive quality standards.

Nice To Haves

Experience in knowledge management, data analytics, or informatics systems.
Familiarity with data visualization tools (e.g., Tableau, Power BI) and their testing.
Experience with cloud-based testing and cloud infrastructure (e.g., AWS, Azure).
Familiarity with test management tools (e.g., Jira, XRay).
Certification in software testing (e.g., ISTQB).

Responsibilities

Quality Assurance Strategy: Develop and implement comprehensive QA strategies for knowledge informatics systems, including data management platforms, reporting tools, and analytics solutions.
Test Planning and Execution: Create and execute detailed test plans, test cases, and automated tests for new and existing applications and systems related to knowledge informatics.
Data Validation: Perform data validation testing to ensure data accuracy, consistency, and integrity across multiple sources and platforms. Identify and report any discrepancies or issues.
Collaboration with Teams: Work closely with data engineers, developers, business analysts, and product owners to identify requirements, ensure alignment on testing objectives, and troubleshoot issues.
Automated Testing: Develop and implement automated testing scripts to ensure consistent testing and improve the efficiency of the QA process. Use appropriate testing tools and frameworks (e.g., Playwright, Cucumber).
System Integration Testing: Conduct integration testing to ensure that various systems, applications, and data flows work seamlessly together, meeting functional requirements and data accuracy standards.
Regulatory Compliance: Ensure that all systems and data management practices are following industry regulations, such as HIPAA, GDPR, or other relevant standards.
Defect Management: Identify, track, and manage defects through the lifecycle, including initial identification, reproduction, resolution, and retesting. Communicate issues to relevant stakeholders and assist in troubleshooting.
Documentation and Reporting: Maintain detailed documentation of test plans, test cases, test results, and defect logs. Provide regular status updates to the project team and stakeholders.
Continuous Improvement: Stay up to date with industry’s best practices, tools, and technologies related to QA and knowledge informatics. Identify opportunities for improving the QA process and increasing test efficiency.