Senior Quality Data Analyst

As a Senior Test Engineer specializing in data analysis and coordination, your role will involve analyzing large datasets to identify quality issues, trends, and opportunities for process improvement. You will be responsible for developing, monitoring, and maintaining data quality metrics, dashboards, and reports. Additionally, you will perform data validation, cleansing, and integrity checks across multiple data sources. Your key responsibilities will include: - Analyzing large datasets to identify quality issues, trends, and opportunities for process improvement. - Developing, monitoring, and maintaining data quality metrics, dashboards, and reports. - Performing data validation, cleansing, and integrity checks across multiple data sources. - Investigating root causes of data quality issues and recommending corrective actions. - Collaborating with business, operations, product, and technology teams to establish data quality standards and governance practices. - Designing and executing quality audits to ensure compliance with organizational and regulatory requirements. - Creating automated reporting solutions and quality monitoring frameworks. - Supporting continuous improvement initiatives through data-driven recommendations. - Documenting data quality processes, controls, and business rules. - Tracking KPIs and SLAs related to data accuracy, completeness, consistency, and timeliness. - Participating in UAT and quality testing activities for new systems, reports, and data pipelines. It is also beneficial to have exposure to Python coding and relevant AI tools. Prior experience or certification in AI tools would be a plus for this role. As a Senior Test Engineer specializing in data analysis and coordination, your role will involve analyzing large datasets to identify quality issues, trends, and opportunities for process improvement. You will be responsible for developing, monitoring, and maintaining data quality metrics, dashboards, and reports. Additionally, you will perform data validation, cleansing, and integrity checks across multiple data sources. Your key responsibilities will include: - Analyzing large datasets to identify quality issues, trends, and opportunities for process improvement. - Developing, monitoring, and maintaining data quality metrics, dashboards, and reports. - Performing data validation, cleansing, and integrity checks across multiple data sources. - Investigating root causes of data quality issues and recommending corrective actions. - Collaborating with business, operations, product, and technology teams to establish data quality standards and governance practices. - Designing and executing quality audits to ensure compliance with organizational and regulatory requirements. - Creating automated reporting solutions and quality monitoring frameworks. - Supporting continuous improvement initiatives through data-driven recommendations. - Documenting data quality processes, controls, and business rules. - Tracking KPIs and SLAs related to data accuracy, completeness, consistency, and timeliness. - Participating in UAT and quality testing activities for new systems, reports, and data pipelines. It is also beneficial to have exposure to Python coding and relevant AI tools. Prior experience or certification in AI tools would be a plus for this role.