Quality Assurance Engineer

Fractal is a strategic AI partner to Fortune 500 companies focused on enhancing human decision-making. The Quality Assurance Engineer will support the deployment and monitoring of quality standards, collaborating with teams to develop a Quality Assurance framework and ensuring consistent quality throughout the data product lifecycle.

Responsibilities:

• Lead and participate within QA teams through management of daily activities, training, and mentoring
• Collaborate with stakeholders to improve quality standards and testing procedures
• Develop test plans, test scenarios, test cases and test data for different testing activities
• Guide testing methodologies across the teams on all different projects
• Provide definition, implementation, and maintenance of standard QA processes and methodologies for cloud, data, and application engineering efforts
• Collaborate with Product Owners and UX/UI Designers teams to understand different use cases and develop test plans accordingly
• Collaborate with Product and Development Leads to develop and implement a testing roadmap for the product
• Work with development teams to develop quality standards for areas such as test automation, unit, functional, system integration, performance, and user acceptance test phases
• Own end-to-end QA automation and manual quality assurance processes and execution
• Define and implement KPI’s to support end-to-end automation in the product development quality lifecycle
• Coordinate and manage platform releases by overseeing test case execution, documenting defects, and managing deployment of releases
• Troubleshoot quality issues and modify test procedures when applicable

Requirements:

• Bachelor's degree in a relevant field such as Information Systems, Computer Science, Engineering, etc
• 3 to 5 years of software testing experience
• 6+ years of experience working as a QA Engineer or in a similar capacity
• Knowledge of QA methodologies, tools, and techniques
• Knowledge of DevOps principles
• Experience working in an Agile environment
• Excellent communication skills and ability to work with the different stakeholders to improve the company's procedures and to ensure the vision is communicated clearly
• Previous experience as test automation engineer at various development stages and integrating with CI/CD pipelines (e.g., unit, integration, load tests)
• Proficiency in Python programming
• Experience with testing PySpark code and API testing
• Experience with test automation frameworks (Python BDD)
• Experience with docker containers
• Analytical thinking, problem-solving skills, and attention to detail
• QA management experience
• Experience working with professional software engineering practices and best practices for the full software development life cycle
• Experience improving product test coverage and effectiveness