Fractal is a strategic AI partner to Fortune 500 companies, aiming to enhance human decision-making in enterprises. The Quality Assurance Engineer will support the deployment and monitoring of quality standards, collaborating with various teams to develop a comprehensive Quality Assurance framework and ensure the delivery of high-quality data products.
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 life cycle
- 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 principals
- 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