Data Quality Lead

Job Summary The Data Quality Lead will be responsible for defining and executing end-to-end testing and business validation strategies for enterprise data products. This role focuses on ensuring comprehensive testing coverage across business use cases, validating data quality and usability, and driving structured User Acceptance Testing (UAT) practices in collaboration with business and technical teams. This is a high-impact role within a rapidly evolving environment where processes and frameworks are still being established. The ideal candidate will have experience building scalable validation frameworks, implementing repeatable testing processes, and supporting enterprise data quality initiatives across cloud-based data platforms. Key Responsibilities Design and implement end-to-end testing strategies for enterprise data products across multiple business domains and use cases. Lead business validation and UAT planning and execution activities, ensuring complete coverage from source systems through final reporting outputs. Develop and standardize testing artifacts including test strategies, test plans, test cases, traceability matrices, defect tracking processes, and validation documentation. Build and maintain data validation and reconciliation frameworks to ensure data accuracy, completeness, consistency, and timeliness. Perform and coordinate data quality testing activities across ingestion, transformation, storage, and reporting layers. Collaborate with business stakeholders to define validation success criteria and expected outcomes. Partner with data engineering teams to understand data transformations, pipelines, and processing logic. Work closely with BI and reporting teams to validate dashboards, metrics, and reporting accuracy. Establish repeatable testing and validation processes within evolving or ambiguous environments. Identify, document, and track data quality issues and defects through resolution. Support continuous improvement initiatives related to data quality, testing standards, and validation methodologies. Ensure alignment between business requirements, technical implementations, and reporting outcomes. Required Qualifications 5-10 years of experience in data validation, business testing, UAT, business analysis, or data quality-related roles. Strong experience leading enterprise-level UAT and end-to-end testing initiatives for data products. Hands-on experience with data validation, reconciliation, and data quality testing practices. Experience working with cloud-based data platforms such as AWS, Azure, or GCP. Experience with enterprise data warehouse environments such as Redshift or similar technologies. Familiarity with BI and reporting tools such as Power BI or Tableau. Strong ability to collaborate effectively across business, analytics, and technical teams. Proven experience designing and implementing testing frameworks and operational processes. Strong analytical, troubleshooting, documentation, and communication skills. Experience validating data across the full lifecycle including ingestion, transformation, storage, and reporting layers. Preferred Qualifications Experience supporting enterprise analytics and reporting data products. Utility or energy industry experience, or strong prior experience in enterprise data quality programs. Knowledge of data quality concepts including profiling, reconciliation, and anomaly detection. Experience validating business metrics within BI tools and semantic data layers. Familiarity with Agile delivery methodologies and enterprise testing practices.