Assistant Manager - Data Governance.TECH -Data Management.MIT

Role Overview

Assistant Manager – Data Governance at Mashreq, within the Data & Analytics / Enterprise Data Management department.

Role Purpose

Lead the Bank's Data Governance and Data Quality capabilities by establishing governance practices, driving stakeholder accountability, improving data quality, and ensuring enterprise data is trusted, governed, and fit for business, regulatory, risk, financial reporting, analytics, and AI use cases. Act as the primary point of coordination for Data Governance and Data Quality across business and technology domains, ensuring adoption of policies, standards, controls, and timely remediation of data-related issues.

Key Responsibilities

Data Governance

• Lead implementation of the Data Governance Framework across the Bank.
• Drive adoption of Data Management policies, standards, procedures, and controls.
• Govern Critical Data Elements, metadata, business glossary, data dictionary, lineage, and data catalog adoption.
• Ensure Data Owners, Data Stewards, and System Owners understand and execute their responsibilities.
• Track governance maturity and drive continuous improvement across business units.

Data Quality

• Own the enterprise Data Quality Framework, standards, rules, controls, and monitoring processes.
• Define and track Data Quality KPIs, thresholds, scorecards, and Data Quality Index performance.
• Monitor Data Quality trends and drive timely remediation of critical and recurring issues.
• Lead root-cause analysis for high-impact data quality problems.
• Report Data Quality risks, progress, and remediation status to management and governance forums.

Stakeholder Management & Accountability

• Act as the primary contact for Data Governance and Data Quality matters across Business, Technology, Risk, Compliance, Finance, Operations, and Audit.
• Hold stakeholders accountable for ownership, stewardship, remediation, and adherence to approved standards.
• Challenge stakeholders constructively where data obligations, controls, or remediation actions are not being fulfilled.
• Lead discussions to resolve cross-functional data ownership, lineage, metadata, and quality issues.
• Lead governance forums and drive closure of agreed actions.

Regulatory, Audit & Risk

• Support regulatory reviews, audits, assurance activities, and risk assessments related to data management.
• Drive remediation of Data Governance and Data Quality findings and control gaps.
• Ensure governance evidence, documentation, controls, and reporting remain audit-ready.
• Partner with Risk, Compliance, Finance, Audit, and Technology to strengthen data controls.

Leadership & Capability Building

• Lead and develop Data Governance and Data Quality resources.
• Coach Data Stewards and governance stakeholders across the organization.
• Operate independently in managing priorities, forums, actions, and stakeholder engagements.
• Promote a culture of accountability, ownership, continuous improvement, automation, and practical delivery.

Qualifications & Experience

• 5+ years in Data Governance, Data Quality, Data Management, Risk Data, Regulatory Data, or Enterprise Information Management.
• Strong experience in banking, financial services, or another regulated industry.
• Experience leading enterprise-wide Data Governance and Data Quality programs.
• Proven ability to influence senior stakeholders, enforce accountability, and drive cross-functional remediation.
• Experience with governance and data quality tools such as Informatica, DEQ, Power BI, Tableau, or equivalent platforms.

Skills & Competencies

• Data Governance frameworks, ownership and stewardship, Critical Data Elements, metadata, glossary, lineage, catalog, and operating model.
• Data Quality rules and controls, profiling, monitoring, dashboards, Data Quality Index, root-cause analysis, and remediation lifecycle.
• Stakeholder influence, governance leadership, executive communication, autonomy, problem solving, and change leadership.

Additional Information

Success measures include improvement in Enterprise Data Quality Index and reduction in critical data issues; increased coverage of governed Critical Data Elements, metadata, glossary, lineage, and Data Quality controls; timely closure of Data Governance and Data Quality remediation actions, audit observations, and risk findings; improved stakeholder adherence to Data Management policies, standards, and governance obligations; stronger governance forum discipline, action closure, and management reporting transparency; and visible uplift in data ownership, stewardship, adoption, and governance maturity across business units.