.Only available for #residents of #MexicoAbout team:You will be part of the Inscape QA team that focuses on quality on front-end embedded client/TV and backend cloud services that report high-quality data to customers. The client QA team tests various embedded clients and firmware for various Vizio TVs. The backend QA team is responsible for validating our award-winning Inscape data set, which millions of people use daily. We have top-notch software engineers, but with this much data, occasionally, there are errors. That's where you come in! We're looking for detail-oriented testers to use our QA team that validates the Inscape data and alerts us of critical bugs and errors before users are affected.What you Will do:Validates data and ETL pipelines to bring new data into a data warehouse.Collaborate with cross-functional teams (Product/Data Science/Data engineering) to develop, execute, and automate data testing processes, ensuring that our data assets meet the highest accuracy, completeness, and consistency standards.Identify and research issues reported by internal and external customers.Manage defect resolution throughout the lifecycle and ensure issues are resolved before production.Develop and execute comprehensive data quality tests to identify anomalies, inconsistencies, and data integrity issues for new product development initiatives, product changes, policy changes, and database changes.Data mining and detailed data analysis on data warehousing systems.Create formal test plans to ensure the delivery of data-related projects involving applications that use ETL components.Provide input and support significant data testing initiatives.Define and track quality assurance metrics such as defects, defect counts, test results, status, and procedures.Verify data accuracy, completeness, and consistency across various data sources and pipelines.Create and maintain test data sets for regression testing.Provide test support for issues requiring code changes or changes made directly to the ETL pipelines.Implement and maintain an automated testing framework for data validation.Continuously improve and expand test coverage through automation.Develop and maintain testing scripts and tools to streamline the testing process.Collaborate with cross-teams to define data validation rules and criteria.Validate data transformations, aggregations, and calculations to ensure accuracy and reliability.Maintain comprehensive documentation of data quality issues and resolutions.Evaluate and transform documentation into test scripts as needed.Work closely with cross-functional teams, including engineers, project managers, and other subject matter experts, to understand data requirements and validation needs.Communicate effectively with stakeholders to report on data quality findings, collaborate on improvements, and identify gaps in test coverage.Schedule or attend peer reviews of test logic to ensure it has been constructed correctly