Data Governance Manager

Sitecore

. Establish and uphold Sitecore’s enterprise data governance framework .

Posted 11/2/2026full-timeKuala Lumpur • MalaysiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in establishing and operationalizing data governance frameworks, ensuring compliance with GDPR and data protection regulations, while implementing security principles and data quality measures across modern data platforms. Proven ability to lead cross-functional collaboration and influence stakeholders in data security and governance initiatives.

Highest-signal resume keywords

Data GovernanceData SecurityData Quality FrameworksMicrosoft FabricMicrosoft Purview

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ProtectionAccess ControlsEncryptionAnomaly DetectionAudit ControlsData RetentionData Lifecycle GovernanceSensitivity LabelsQuality RulesRegulatory Compliance

Soft Skills

LeadershipAnalytical SkillsProblem-SolvingCommunicationCollaboration

Tools & Technologies

Microsoft FabricMicrosoft PurviewAzureAWSGCP

Industry Keywords

GDPRData Protection ActEU AI ActSOC2NIST

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformSitecoreSnowflake

About the role

Key responsibilities & impact

Establish and uphold Sitecore’s enterprise data governance framework
Lead operationalisation of data governance practices across data security, data protection, and data quality within Microsoft Fabric
Define and apply security principles across Microsoft Fabric data sources with Information Security
Implement security guidelines and access controls for governed, auditable, least-privilege data access
Apply access controls, sensitivity labels, encryption, masking, and role-based access
Review and optimise roles and cross-team access
Assess security implications of Agentic AI initiatives and machine learning use cases
Ensure Fabric Lakehouse compliance with GDPR, privacy-by-design principles, and internal privacy and retention policies
Establish and maintain data retention and lifecycle governance
Operationalise Microsoft Purview for classification, retention, sensitivity, and policy enforcement
Establish enterprise-wide data quality frameworks across datasets, aggregated layers, semantic models, and pipelines
Implement quality rules, validation checks, thresholds, anomaly detection, and automated alerting
Monitor data volume trends and system health metrics
Collaborate with Data Engineering to resolve data quality issues
Implement audit controls and ongoing monitoring of user activity and access anomalies
Maintain governance documentation and support audit readiness
Partner with Information Security, Data Protection, Data Engineering, and business stakeholders
Enable secure, compliant, high-quality self-service analytics, AI, and data science
Contribute to governance playbooks, standards, and scalable best practices

Requirements

What you’ll need

8+ 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
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, or GCP, particularly 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
Strategic mindset with strong analytical and problem-solving skills
Excellent communication and documentation skills
Knowledge of relevant regulatory requirements such as GDPR, Data Protection Act, or EU AI Act and industry frameworks such as SOC2 or NIST
Understanding of governance considerations for AI, Copilot, agentic automation, and self-service analytics
Experience with AI practices, data engineering, or data management