Data Governance Manager Kuala Lumpur, Malaysia
Sitecore Lihat semua pekerjaan
- Kuala Lumpur
- Tetap
- Sepenuh masa
- Partner with InfoSec to define and apply the required security principles across all Microsoft Fabric data sources.
- Lead the implementation of robust data security guidelines and access controls to ensure governed, auditable, and least privilege access to data.
- Apply granular security controls such as access controls, sensitivity labels, encryption, masking, and role-based access to safeguard sensitive data assets.
- Review and optimise current roles and cross-team access to maintain secure and scalable data accessibility.
- Assess and manage the security implications of Agentic AI initiatives (ex. Fabric Data Agents, Copilot Agents) and machine learning use cases.
- Ensure Fabric Lakehouse compliance with GDPR, privacy-by-design principles, and internal privacy and retention policies throughout the data lifecycle.
- Champion lawful processing, data minimisation, and transparency, ensuring compliance with regulations while enabling effective data utilisation.
- Establish and maintain data retention and lifecycle governance, ensuring alignment with regulatory and legal requirements.
- Partner with Data Protection and InfoSec to ensure that privacy expectations and obligations are consistently met.
- Operationalise Microsoft Purview for classification, retention, sensitivity, and policy enforcement across the enterprise.
- Establish enterprise-wide data quality frameworks across granular datasets, aggregated layers, semantic models, and pipelines.
- Implement data quality rules, validation checks, thresholds, anomaly detection, and automated alerting to proactively identify and resolve issues.
- Monitor data volume trends and system health metrics to ensure reliable and high-quality data for analytics, reporting, and AI workloads.
- Collaborate with Data Engineering to resolve issues related to accuracy, completeness, timeliness, and consistency.
- Implementing rigorous audit controls across data processes to ensure validity, security, and traceability of data assets.
- Implement ongoing monitoring and audits of user activity and access anomalies across Fabric and integrated environments.
- Produce and maintain governance documentation, supporting audit readiness and demonstrating compliance with internal and regulatory standards.
- Partner with Information Security, Data Protection, Data Engineering, and business stakeholders to align governance framework with organisational needs.
- Enable self-service analytics, AI, and data science by ensuring that underlying data is secure, compliant, and high-quality.
- Contribute to governance playbooks, standards, and scalable best practices.
- 10+ years of experience in data governance, data security, data protection/privacy, data quality, or enterprise data management, with at least 2 years in people management.
- Bachelor's degree in computer science, IT, or a related field.
- Demonstrated leadership in data security and access governance, including multi-layer security, encryption, masking, sensitivity labels, and least-privilege principles across distributed data platforms.
- Experience designing and operationalising data quality frameworks, including rules, checks, thresholds, automated alerts, and anomaly detection across multiple data layers.
- Good experience in audit, monitoring, traceability, and regulatory compliance processes, with the ability to design and maintain scalable governance controls.
- Hands-on experience with Microsoft Fabric or similar modern data platforms such as Databricks or Snowflake.
- Proficiency with Microsoft Purview for lineage, classification, sensitivity, retention management, and policy enforcement or similar tools or frameworks.
- Experience with cloud platforms such as Azure, AWS, GCP, particularly in areas related to security models, identity, storage governance, and data access patterns.
- Proven ability to influence and collaborate with senior stakeholders across security, legal, engineering, and business functions.
- A strategic mindset with strong analytical and problem-solving skills, capable of translating regulatory and organisational requirements into scalable processes.
- Excellent communication and documentation skills, able to articulate governance standards, expectations, and decision-making clearly and effectively.
- Knowledge of relevant regulatory requirements (e.g., GDPR, Data Protection Act, EU AI Act) and industry frameworks (e.g., SOC2, NIST) or similar compliance standards.
- Good understanding of governance considerations for AI, Copilot, agentic automation, and self-service analytics, including responsible data use and risk management.
- Experience with AI practices, data engineering, or data management.