Join EY's AI & Data team as a Manager specializing in Data Strategy and Governance. This role is key to our Consulting Services unit, providing integrated solutions to financial institutions and capital markets participants. You will address complex challenges and leverage data to enhance client business outcomes, fostering a culture of data-driven decision-making.

We seek an expert with 9-12 years of experience in data strategy and governance, possessing a strong understanding of the financial services domain. As a Subject Matter Expert within the EY GDS AI & Data team, you will lead impactful Data Governance and Strategy projects.

Lead and guide Data Governance and Data Strategy engagements, fostering collaboration with cross-functional teams and senior stakeholders. Develop comprehensive data strategies and roadmaps, ensuring alignment with business objectives across various units. Independently architect and design robust data governance frameworks and strategic initiatives. Provide thought leadership and disseminate best practices in data strategy, governance, and management to both clients and internal teams. Effectively communicate and interface with onsite/client contacts and executive leadership, delivering timely status updates and strategic insights.

The ideal candidate possesses 9-12 years of experience in Data Governance processes and frameworks. You should have a proven track record in defining holistic data strategies and roadmaps for large clients. Familiarity with policies, processes, frameworks, and tools for managing enterprise data assets, including master data, reference data, and metadata, is essential. Experience in defining data governance operating models, encompassing data ownership, stewardship, decision rights, governance councils, and RACI structures, is required. A strong understanding of data quality management, including profiling, rule definition, issue management, root-cause analysis, remediation workflows, and governance KPIs, is crucial. Hands-on knowledge of metadata management, business glossaries, data cataloguing, data lineage, and impact analysis is necessary to enhance data discoverability, trust, and regulatory traceability.

Aligning data strategy with business value drivers, regulatory expectations, risk management priorities, target-state data architecture, and measurable transformation roadmaps is a key requirement. Exposure to data privacy, security, retention, access control, and regulatory compliance considerations within financial services data ecosystems is expected. Driving governance adoption through stakeholder workshops, data literacy initiatives, change management, playbooks, reusable templates, and executive-level reporting is vital. You must have hands-on experience implementing at least one end-to-end Data Governance solution using tools like Collibra, Informatica, or Alation. A thorough understanding and experience of software development best practices are also required. Demonstrate a keen eye for value-adds and asset creation to facilitate process reusability and automation.