Senior Data Governance Consultant

We are looking for a senior data governance consultant with a strong technical background to support a strategic data governance and data management project in Saudi Arabia.

This role combines standards development, operationalization of policies through direct engagement, and technical implementation. The ideal candidate can flexibly translate governance concepts into practical operating models, data controls, metadata practices, data quality rules, stewardship workflows, and business-facing recommendations.

The role requires an individual with strong consulting experience who understands the Saudi data governance landscape, including the National Data Management Office (NDMO) and National Data Index (NDI) expectations, and can explain how data governance domains connect across business processes, systems, data ownership, data quality, metadata, classification, access, privacy, reporting, and operational decision-making.

Data Sentinel is a technology and advisory company focused on data and AI trust. Our platform helps organizations discover, understand, govern, and protect data across complex environments, while our advisory team helps clients operationalize data governance, privacy, data management, and AI readiness in a practical way.

For this engagement, Data Sentinel is supporting the client with the operating model, governance practices, technical enablement, and business-facing adoption needed to move from standards and policies into day-to-day execution.

You will work directly with business stakeholders, data owners, data stewards, IT teams, data engineers, architects, and governance leadership to help operationalize data governance across the organization.

Key responsibilities include:

• Support the implementation and operationalization of data governance practices aligned to NDMO / NDI expectations and industry best practices.
• Help define and document data ownership, stewardship roles, governance workflows, and decision-making forums.
• Work with business teams to understand critical data elements, business terms, data issues, reporting needs, and operational pain points.
• Translate business requirements into practical data governance, metadata, lineage, data quality, and architecture requirements.
• Create and refine data catalogs, business glossaries, metadata standards, lineage views, and data quality rules.
• Help map governance controls to practical evidence, activities, workflows, dashboards, and remediation actions.
• Facilitate workshops with business and technical stakeholders.
• Advise on how NDMO domains connect from a governance perspective
• Support maturity assessments, gap analysis, remediation planning, and executive reporting.
• Help convert governance concepts into clear business-facing outputs that leadership can understand and act on.
• Work with data platform, catalog, quality, or governance tools where applicable.

The successful candidate should have:

• 8+ years of experience across data governance, data management, data architecture, data engineering, business analysis, or related fields.
• Strong working knowledge of NDMO / NDI concepts in Saudi Arabia.
• Practical understanding of how governance domains connect across the enterprise, not just theoretical knowledge of the framework.
• Experience with data catalog, metadata management, business glossary, lineage, data quality, data classification, and stewardship processes.
• Ability to work with both business and technical teams.
• Strong communication skills at the leadership/executive level;
  Selfstarter/independent worker with consulting experience, including workshop facilitation, stakeholder management, requirements gathering, executive communication, and structured problem-solving.
• Ability to create clear documentation, governance artifacts, business-facing summaries, and remediation plans.
• Experience working in complex enterprise environments with multiple stakeholder groups.

Strong candidates should have experience with some of the following:

• Data governance and data catalog tools such as Microsoft Purview, Informatica, or similar platforms.
• Data quality tools such as Informatica Data Quality / Cloud Data Quality or equivalent.
• Metadata, lineage, cataloging, and glossary implementation.
• Data classification, access control, RBAC, masking, retention, archival, and privacy related controls.
• Dashboarding, scorecards, KPI reporting, or governance metrics.
• Familiarity with the appropriate use of AI tools to support governance, deliverables, and outputs.

This role requires someone who can operate confidently in business conversations.

The candidate must be able to:

• Lead structured conversations with senior stakeholders.
• Ask strong discovery questions.
• Separate symptoms from root causes.
• Explain technical and governance concepts in plain business language.
• Build trust with business users, data owners, IT teams, and leadership.
• Push work forward without creating unnecessary friction.
• Convert ambiguity into…