Victor Cernei

Advised clients on data governance strategy, data quality improvement, and information modeling. Supported the design of data governance processes, including stewardship, validation workflows, and escalation paths. Developed information models and business glossaries to harmonize data usage across departments. Assisted organizations in building a data-driven culture, linking governance objectives with business value. Delivered governance documentation, policies, and standards aligned with best practices.

Actively contributed to the implementation of data governance practices within financial and banking platforms. Defined and documented data quality rules, validation controls, and completeness checks for financial and transactional data. Supported the creation of conceptual data models and information models to standardize financial entities, reference data, and reconciliation objects. Worked closely with business and IT stakeholders to clarify data ownership, responsibilities, and governance processes. Used SQL to analyze data quality issues, detect inconsistencies, and support remediation actions. Developed Power BI dashboards to monitor data quality KPIs and operational data health. Contributed to governance documentation, standards, and best practices in collaborative environments.

Supported the establishment of data governance standards during ERP and data platform transformations. Defined data quality policies, master data rules, and validation logic across finance, logistics, and sales domains. Designed conceptual and logical data models to align business processes with system data structures. Collaborated with business users to define common data definitions and business terminology, contributing to a shared information framework. Implemented data quality monitoring using SQL and Power BI, enabling continuous improvement initiatives. Worked in close collaboration with cross-functional teams (IT, Finance, Operations).

Worked in large, structured organizations with strict data governance, quality, and compliance requirements. Defined and maintained data standards, controls, and documentation for financial and operational data. Supported information modeling and reporting in secure environments. Used SQL and BI tools to ensure data accuracy, consistency, and traceability.