Data Quality Engineer

Data Quality Engineer
Responsibilities:
Partner with the system test organization and each of the asset testing groups to develop an overall integration and validation plan across the ecosystem (firmware, cloud, and clients) for each feature
Collaborate with the ecosystem TPM to determine areas of integration risks between subsystems and schedules for when each of the component integrations can and should be qualified
Coordinate execution of manual tests as necessary to validate successful integration
Create automated tests (in partnership with test writing teams) to be used as both feature functionality verification and regression as features are developed
Ensure needed automation capability needs are communicated to ecosystem tools development team to be able to automate needed coverage
Analyze and review new product and solution designs and specifications for potential quality issues; provide tangible feedback and propose changes to improve product quality and minimize risk of failures
Review reports, test data, and process results for assigned components and subsystems to identify trends and issues, perform root-cause analysis, and develop recommendations for resolution
Participate in the design of the features with integration qualification in mind
Knowledge and Skills:
EAWS, Python / Pytest / pip / virtual environments, Azure Dev Ops scripted pipelines, GitHub, Windows and Linux Shell Scripting, REST APIs
Strong analytical and problem-solving skills
Software systems testing methodology, including writing and execution of test plans, debugging, and testing scripts and tools
Excellent written and verbal communication skills. Ability to effectively communicate product architectures, design proposals and negotiate options at management levels
Agile / Scrum methodologies