Analytics Staff Quality Assurance Engineer job in Washington, DC| Recruit Arrow
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Analytics Staff Quality Assurance Engineer
Location : District of Columbia, Washington
Refer job # ALNO339486
Job Responsibilities and Requirements: Essential Responsibilities: In the role of Staff Quality Assurance Engineer - Analytics, you will: Own large sized tasks or small projects and delivers QE artifacts. Manages deliverables and mentors junior team members Contribute in driving initiatives such as defining coding standards and processes to ensure quality code is produced Appropriately reuse existing code wherever possible; drives same behaviors across team while coaching other developers to improve their code quality Develop and enhance the test infrastructure and continuous integration framework used across teams at the COE Determine testing best practices and principals and promotes them across the organization Be an expert in developing and executing maintainable automation tests for acceptance, functional, and regression test cases Be skilled at developing code for other developers to learn from Be skilled in integrating project testing with continuous-integration process Work with fellow team members to diagnose bugs and formulate solutions Provide functional and technical expertise in bug fixes Act as an expert in the quality engineering, manages test plans and testing methodology for software projects Uses test automation techniques (data driven, pairwise, mocking, test hooks) that fit the problem space. Understands designing and coding for testability to produce quality code with the lowest cost Has significant experience in conducting test in analytics, including deep learning platforms such as TensorFlow, Caffe, Keras, as well as GPU load balancing and memory management Has work in areas of data science, machine learning and computer vision and understand the flow and ebb of advanced analytics to be able to lead QA for the analytics team Qualifications/Requirements: Bachelors Degree in Computer Science or STEM Majors (Science, Technology, Engineering and Math) from an accredited college or university Minimum 6 years of experience in Software Testing OR Masters degree in Computer Science or STEM Majors (Science, Technology, Engineering and Math) from an accredited college or university with a minimum 4 years of experience in Software Testing OR PhD in Computer Science or STEM Majors (Science, Technology, Engineering and Math) from an accredited college or university with a minimum 2 years of experience Software testing Eligibility Requirements: Legal authorization to work in the U.S. is required. GE may agree to sponsor an individual for an employment visa now or in the future if there is a shortage of individuals with particular skills Desired Characteristics: Experience writing test scenarios and executing tests, manually and with test automation tools Experience developing automated tests using automation frameworks Experience using automation frameworks like Selenium and Protractor preferred Strong coding skills with development experience in the Predix stack preferred Effective written and verbal communication Excellent analytical abilities to grasp the key points from complicated requirements and business processes Ability to manage and prioritize multiple assigned tasks Strong trouble-shooting skills to debug issues, determine root cause, and identify coverage gaps Passion for quality and representing the voice of our customers Experience with and understanding of white-box testing techniques as applied to test automation Appreciation for and experience with types of manual testing such as end-to-end and exploratory testing Expert-level experience with the QA function across SDLC in an agile development environment Strong experience with end-to-end SDLC, testing methodologies and test phases, including unit, assembly, system, integration, regression and performance testing Ability to create accurate and detailed test-cases and test scripts Ability to analyze and translate requirements and development stories into test scripts Strong working knowledge of QA processes and methodologies.
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