A global financial-services organization is expanding its data-quality and governance capabilities within a growing cybersecurity data environment. This hands-on implementation role will help establish stronger controls over how critical security and risk data is defined, validated, monitored, and governed across a data lakehouse. The specialist will work with data owners, stewards, engineers, analysts, and governance stakeholders to convert business requirements into functioning data-quality rules and technical controls. This is not a high-level governance-policy position. The successful candidate must be comfortable configuring Collibra, working in Databricks, writing SQL, testing rules, and investigating data problems directly. RESPONSIBILITIES Design, configure, implement, and monitor enterprise data-quality rules in CollibraWork hands-on with Collibra Data Quality and Collibra Data Intelligence PlatformPartner with data owners and stewards to identify critical data elementsTranslate business and governance requirements into measurable technical controlsProfile datasets for completeness, consistency, validity, and accuracyUse SQL to validate rules, reconcile datasets, investigate anomalies, and troubleshoot failuresWork with Databricks-based cybersecurity and risk datasetsTest data-quality logic through QA and UAT processesCreate and maintain test cases, test plans, scripts, rule inventories, and validation documentationInvestigate false positives and unexpected rule resultsMonitor data-quality coverage and control effectivenessSupport data lineage, metadata, master-data, and reference-data practicesHelp mature the broader cybersecurity data-governance programContribute to customized governance and data-quality solutions Role Requirements: Strong hands-on Collibra implementation experienceExperience with Collibra Data QualityExperience with Collibra Data Intelligence PlatformHands-on Databricks experienceStrong SQL for profiling, validation, reconciliation, and troubleshootingExperience personally building and configuring data-quality rulesAbility to translate requirements into executable data-quality controlsExperience with data profiling, anomaly investigation, and rule testingUnderstanding of critical data elements and data-quality dimensionsExperience partnering with data owners, data stewards, developers, engineers, and analystsQA and UAT experience related to data-quality implementationsUnderstanding of enterprise data governance, metadata, master data, reference data, and lineageAbility to work effectively in a technical, customized governance environmentAbility to work onsite in Charlotte three days per week PREFERRED EXPERIENCE PythonCybersecurity, cyber-risk, or technology-risk dataFinancial-services or regulated-industry experienceData-lakehouse experienceData-lineage and metadata-management experienceExperience developing customized functionality around governance platformsExperience supporting a federated data-governance model