Data Governance / Project Manager

Description

Summary: The Project Manager leads end-to-end delivery of initiatives, ensuring alignment with business strategy, regulatory requirements, and digital goals. Highlights: 1. Lead end-to-end delivery of strategic initiatives 2. Oversee metadata management and data cataloging 3. Drive data quality management and governance workflows **Scope of Work – Data Governance** **/ Project Manager** The Project Manager is responsible for leading the end\-to\-end delivery of assigned initiatives, ensuring alignment with the Group's business strategy, regulatory requirements, and digital goals. 1\. Metadata Management \& Data Catalog * Centralized, searchable data catalog covering data assets across on‑prem, cloud, and hybrid environments * Automated metadata discovery and harvesting * Business and technical metadata support, including data definitions, ownership, and usage context * Ability to document and manage data products and critical data elements 2\. Data Lineage \& Impact Analysis * End‑to‑end, preferably automated, data lineage (source‑to‑target) * Visual lineage for business and technical users * Impact analysis to assess downstream effects of changes to data, models, or systems * Support for SQL, ETL, ELT, BI, and analytics pipelines 3\. Data Quality Management * Definition and monitoring of data quality rules and thresholds * Support for profiling, validation, and exception management * Data quality dashboards and scorecards * Workflow for issue remediation and accountability 4\. Governance, Stewardship \& Workflow * Clearly defined governance roles (e.g., Data Owner, Data Steward, Custodian) * Configurable workflows for approvals, certifications, and issue management * Policy management and enforcement capabilities * Evidence and audit trail for governance decisions 5\. Security, Privacy \& Compliance * Classification of sensitive and regulated data (e.g., PII, confidential data) * Integration with enterprise Identity Access Management for role‑based access control * Support for privacy regulations and internal data policies * Data access transparency and auditability 6\. AI \& Analytics Enablement * Support for AI‑ready data governance, including datasets, features, and models * Trust, explainability, and lineage for AI and advanced analytics use cases * Alignment with responsible and ethical AI principles * Integration with analytics and machine learning platforms 7\. Integration \& Interoperability * Native connectors or APIs for data platforms (cloud warehouses, lakes, ETL tools, BI, ML platforms) * Open architecture to avoid vendor lock‑in * Ability to integrate with existing enterprise architecture and tooling 8\. Scalability \& Performance * Proven capability to scale across large data estates and multiple domains * Support for enterprise‑wide deployment and federated governance models * High availability, reliability, and performance 9\. Usability \& Adoption * Intuitive user experience for both technical and business users * Self‑service capabilities with appropriate controls * Collaboration features (comments, annotations, ownership visibility) 10\. Reporting \& Metrics * Governance KPIs and dashboards (e.g., data quality, adoption, compliance) * Executive‑level reporting capabilities * Custom reporting and export options Job Types: Full\-time, Contract Contract length: 12 months Pay: BD1,000\.000 \- BD2,500\.000 per month Work Location: In person