Lead Data Management & Governance

THE COMPANY

Singlife Philippines is a mobile-first life insurance company on a mission to make financial independence achievable for every Filipino.

Through modern technology, we provide insights, guidance, and solutions—all via mobile devices—so Filipinos can get the right financial protection when they need it. From emergencies and loss of income to high medical bills and future goals like education or retirement, Singlife ensures money is there when it matters most

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As a subsidiary of Singlife Singapore, we combine the agility of a start-up with the strength of a trusted regional brand. Through our growing portfolio of partnerships,including trusted platforms like GCash, AUB's HelloMoney, and Hello Pag-IBIG, we're making meaningful insurance more accessible to the wider market.

At Singlife, we're not just building products. We're democratizing access to financial protection, one Filipino at a time.

Job Summary:

The Senior Manager – Data Management & Governance is accountable for establishing, operating, and continuously improving the organization's enterprise data governance, data management, and data quality framework.

This role ensures that data is trusted, secure, compliant, discoverable, and fit-for-purpose across operational systems, analytics platforms, and digital channels. It is the executive owner of data policies, standards, data ownership, data quality management, metadata, lineage, and regulatory data controls.

The role partners closely with Business, IT, Risk, Compliance, Architecture, and Analytics teams to institutionalize data as a strategic enterprise asset while ensuring compliance with data privacy laws, regulatory requirements, and internal control frameworks.

Key Responsibilities:

Data Governance Framework & Operating Model

• Define, implement, and operate the enterprise data governance framework including:
• Data ownership and stewardship model
• Data domains and critical data elements (CDEs)
• Data policies, standards, and procedures
• Establish and run the Data Governance Council and domain working groups.
• Ensure governance is embedded into delivery, operations, and change processes.

Data Management & Standards

• Own and enforce standards for:
• Master data
• Reference data
• Transactional data
• Analytical data
• Define:
• Data lifecycle management
• Data classification and handling
• Retention and archiving policies
• Ensure consistent data definitions across systems and platforms.

Data Quality Management

• Define and implement:
• Enterprise data quality framework
• Data quality rules, thresholds, and controls
• Data quality monitoring and dashboards
• Own:
• Data issue management process
• Root cause analysis and remediation tracking
• Ensure data quality is proactively measured and continuously improved.

Metadata, Lineage & Data Catalog

• Own enterprise:
• Business glossary
• Technical metadata
• Data lineage
• Data catalog capabilities
• Ensure:
• Traceability from source to consumption
• Transparency for regulatory and audit requirements
• Promote self-service data discovery and understanding.

Regulatory, Privacy & Compliance Data Controls

• Ensure compliance with:
• Data Privacy Act / GDPR
• Insurance / banking regulatory requirements
• Internal audit and risk policies
• Define and enforce:
• Data access controls
• Data masking and anonymization
• Consent and purpose limitation controls
• Act as data governance lead during audits and regulatory reviews.

Data Architecture & Platform Alignment

• Partner with:
• Enterprise Architecture
• Data Platform teams
• Application teams
• Ensure:
• Governance is embedded into data pipelines, DWH, lakehouse, and integration layers
• New systems and platforms comply with data standards by design
• Enforce governance-by-design, not governance-after-the-fact.

Operating Model, Adoption & Change

• Build and lead:
• Data governance office / team
• Data stewards community
• Drive:
• Training and awareness
• Cultural adoption of data ownership
• Embed data governance into:
• SDLC
• Change management
• Procurement and vendor onboarding

Metrics, Reporting & Continuous Improvement

• Define and report:
• Data quality KPIs
• Governance adoption metrics
• Compliance metrics
• Produce executive dashboards on data health and risk posture.
• Drive a continuous improvement roadmap for data management maturity.

Qualifications:

• Bachelor's degree in Information Systems, Computer Science, Data, or related field.
• 10+ years experience in:
• Data management
• Data governance
• Data quality
• Analytics or enterprise systems
• 5+ years in senior or enterprise leadership roles in data or technology.
• Strong experience in:
• Data governance frameworks (DAMA, DCAM, etc.)
• Data quality management
• Metadata and lineage
• Regulatory data management
• Experience in regulated industries (insurance, banking, financial services).

Preferred Qualifications:

• Master's degree in Data, IT, or Business
• DAMA-DMBOK, DCAM, or similar certifications
• Experience with:
• Data catalogs
• Data quality tools
• Master data management platforms
• Experience with:
• Cloud data platforms
• Modern data stack (DWH, lakehouse, streaming, BI)

Leadership Competencies:

• Strong governance mindset balanced with pragmatism
• Influential, consensus-building leadership style
• Highly structured, policy- and control-oriented
• Strong business and regulatory communication skills
• Change leadership and cultural transformation capability
• Executive-level stakeholder management