Manage the development lifecycle and resources across all data quality initiativesImplement data quality processes including translation, parsing, analysis, standardization, and enrichment at point of entry, batch, and real time modesDesign, develop, test, deploy and document data quality procedures/mappings and outputs that will run in a scheduled, batch, or real-time environmentCreate metrics to evaluate data accuracy, consistency, and relevance. Identify and employ statistical methods relevant to data quality testingDevelop and implement scorecards to monitor data quality program performance. Identify causes of errors or discrepancies in data collection and recommending solutionsContribute to data culture by promoting data quality awareness and ensure that data pipelines adhere to quality standards