Validator

Join Three Percent as a Validator responsible for ensuring data accuracy and integrity across various projects. This role requires a sharp eye for detail and the capability to perform thorough data verification and validation activities. The Validator plays a critical part in maintaining the quality of data inputs by employing quality assurance frameworks, risk assessment techniques, and process improvements, ensuring that data meets the highest standards before it reaches production or analysis stages. The ideal candidate has a minimum of two years of experience in validation and is proficient at using data validation tools and techniques including ETL tools, statistical analysis methods, and automated testing tools such as TestNG and Selenium. As a Validator at Three Percent, you focus on collaborating with cross-functional teams to identify potential data quality issues early and to develop effective solutions. The role demands strong analytical thinking to assess risk and improve validation processes continuously. Excellent communication skills are necessary to report findings clearly and to work with stakeholders in process improvements aimed at maintaining compliance and enhancing the organization's data quality management. This position does not involve managing a team but requires a proactive approach to contribute to quality assurance and continuous integration initiatives.
Responsibilities

Conduct thorough data verification and validation to ensure accuracy and completeness of datasets before approval.
Apply quality assurance frameworks and risk assessment techniques to identify and resolve data quality issues.
Utilize ETL tools and data validation techniques to support data cleansing and transformation processes.
Perform statistical analysis to detect trends, inconsistencies, and potential risks within datasets.
Develop, execute, and maintain automated tests using tools such as TestNG and Selenium to support continuous integration pipelines.
Collaborate with cross-functional teams to communicate data validation findings and recommend process improvements.
Maintain comprehensive documentation of validation procedures, outcomes, and quality metrics.
Implement and monitor data quality management practices to align with organizational standards and compliance requirements.
Review new data inputs and data changes continuously to prevent errors before impacting downstream processes.
Support the development and enhancement of validation methodologies to increase efficiency and accuracy.