Navy Federal Credit Union - Vienna, VA
posted 3 months ago
The Savings and Membership Data Governance team is part of the Project Systems and Technology team within the Savings and Membership department at Navy Federal Credit Union. The primary mission of this team is to drive data excellence by maximizing the value of data as a reliable and trusted business asset while promoting responsible data management practices. This involves ensuring that data is well managed and that data risk is minimized. The team focuses on empowering the Savings and Membership Department (SMD) to leverage data assets for effective business insights, partnering with key stakeholders to enhance data management capabilities, and driving accountability and ownership of enterprise data assets. Additionally, the team is committed to building transparency and auditability into policies, practices, and processes, as well as measuring program and business value while reporting on data risks. In alignment with the SMD Data Governance 2024 Road Map, the team will continue to work on several key projects in 2025. These projects include the ongoing development of a comprehensive metadata collection for prioritized SMD systems, building the SMD system architecture to facilitate communication between systems, identifying data errors, patterns, and trends to enhance decision-making, and performing validation checks for business unit reports and dashboards during the transition to cloud technologies. The team will also engage in complex analytical statistical modeling and visualizations on large data sets to support various business operations and organizational objectives. The role involves supporting Business Data Stewards in documenting data dictionaries, managing the technical aspects of the business area's data catalog, and ensuring continuous improvements in data quality and classification. The position also requires enabling data lineage collection and visualization to provide insights on data flows between various producers and consumers of business area data.