Join EY and build a career that is as unique as you are. Leverage global scale, support, an inclusive culture, and cutting-edge technology to become your best self. Your distinct voice and perspective are vital to EY's continued growth and to shaping a better working world for everyone. This senior role focuses on designing and implementing enterprise data governance frameworks, controls, and processes to ensure data quality, integrity, security, and compliance. You will lead key initiatives in Data Quality, Metadata Management, Data Lineage, Data Catalog, and MDM, fostering collaboration with business and technology teams to enhance data governance capabilities and meet regulatory demands. Committed to quality, you will ensure high standards in all work, with thorough reviews by senior colleagues, and contribute to a positive learning environment for the team.

Lead the design and implementation of enterprise data governance frameworks, policies, standards, and controls to ensure trusted, secure, and compliant data across business domains. Spearhead data governance initiatives encompassing Data Quality, Metadata Management, Data Lineage, Data Catalog, and Master Data Management (MDM). Establish robust data quality rules, monitoring mechanisms, validation frameworks, and remediation strategies to enhance data accuracy, consistency, and reliability. Conduct data profiling, reconciliation, root cause analysis, and governance assessments to identify and resolve data-related issues. Maintain comprehensive business glossaries, metadata repositories, data catalogs, and lineage documentation to improve data discoverability and transparency. Implement governance controls throughout the data lifecycle, ensuring adherence to data privacy, security, and regulatory requirements. Collaborate effectively with business stakeholders, data stewards, data owners, architects, analysts, and engineering teams to promote governance adoption and refine data management practices.

A minimum of 4 years of experience in Data Governance, Data Quality, Metadata Management, Data Management, or Data Engineering is essential. A strong grasp of Data Governance principles, frameworks, and best practices is required. Proven experience in implementing Data Quality controls, monitoring, and remediation processes is necessary. Expertise in metadata management, data lineage, business glossary, data catalog, and MDM concepts and governance principles is critical. Proficiency in data profiling, validation, reconciliation, and root cause analysis is expected. Familiarity with cloud data platforms like Microsoft Fabric, Databricks, Azure Data Lake, or Snowflake is important. Experience with Data Governance tools such as Microsoft Purview, Informatica IDMC, Collibra, or Alation is beneficial. Strong SQL skills and experience with Python or PySpark for automation are required. An understanding of data privacy, security, regulatory compliance, and information management controls is necessary. Experience with collaboration tools like Jira, Azure DevOps, Confluence, and SharePoint is valued. A solid understanding of data lifecycle management and data stewardship practices is expected. Experience in driving governance maturity assessments, developing roadmaps, and creating governance KPIs, dashboards, and executive reporting is a plus.