Senior Data Quality Analyst – Cybersecurity Data Governance #3593664

Join a global financial services technology environment supporting a critical cybersecurity data initiative. This team is focused on strengthening security and risk data platforms by centralizing information security data, improving governance, and creating trusted data lineage across enterprise sources. The role sits within a collaborative, cross-functional setting that works closely with developers, data owners, governance leads, business analysts, and technology stakeholders to improve the quality and reliability of cybersecurity data.

This is a hybrid opportunity based in Charlotte, North Carolina, supporting a high-visibility cybersecurity data warehouse and governance initiative. The role offers the opportunity to influence enterprise data quality standards, work with modern data governance tooling, and contribute to a strategic data platform supporting information security and risk reporting.

• Define and create data quality rules for cybersecurity and information security data sources.
• Partner with data owners, data stewards, and stakeholders to identify Key Data Elements and data quality requirements.
• Support the development of trusted cybersecurity metrics and dashboard-ready data fields.
• Perform data validation, reconciliation, QA, and UAT to confirm data quality rule accuracy and effectiveness.
• Create and maintain test plans, test cases, and test scripts to validate data quality results.
• Collaborate with technology, governance, and business teams to improve data integrity, lineage, and governance across enterprise systems.
• Track rule coverage, effectiveness, and ongoing data quality improvements across security-related platforms.

• 10+ years of relevant experience in data analysis, data quality, data governance, or enterprise data management.
• Strong experience defining, testing, and deploying data quality rules across complex enterprise systems.
• Hands-on experience with Collibra DIP and Collibra Data Quality / CDQ products.
• Strong knowledge of data profiling, validation, reconciliation, and data quality monitoring tools.
• Proficiency in SQL or rule-based engines used to implement validation logic.
• Understanding of master data management and reference data management concepts.
• Experience working with Key Data Elements, data owners, data stewards, governance leads, and business stakeholders.
• Ability to create detailed test plans, execute test cases, support QA/UAT, and validate data quality outcomes.
• Strong communication, analytical thinking, stakeholder management, and documentation skills.
• Cybersecurity, risk, financial services, or regulated enterprise data experience is highly preferred.