Data Management & Governance Program Lead

Job title: Data Management & Governance Program Lead

Engagement: Enterprise data management programme for a life insurer: KPI standardization, data governance, data quality and lineage, platform assessment, growth analytics, AI readiness and BAU handover

Location: Manila, Philippines (hybrid) – to confirm

Reports to: Engagement Director (vendor); works day to day with the client’s Deputy CTO

Leads: Project Manager, Project Coordinator and client EDO technical leads (BI, Snowflake, Power BI)

Experience: 12–15+ years in data and analytics; 5+ years leading data governance or data management programmes

Purpose of the role

The Program Lead designs, gets approved and hands over a complete data management framework, so the business trusts its numbers and can run it without the vendor after Go-Live.

The role owns nine strategic deliverables, from KPI definitions to BAU transition, and steers the client’s EDO team on day-to-day data operations and dashboard delivery. Success means one agreed meaning for every KPI, a named owner for every data asset, proven data quality, and a client team that runs it all on its own.

Key responsibilities

Strategy and frameworks

- Write and maintain the data management frameworks: KPI standardization, data governance, data quality and lineage, platform assessment, growth analytics, AI and automation readiness, handover, committee governance and BAU transition.
- Present frameworks and decision papers to the Steering Committee, the Data Management Committee and the Design Authority, and secure approval at each gate.

KPIs and data governance

- Run KPI definition workshops with each department; agree one definition, formula and owner per KPI; build the KPI Dictionary.
- Set up the governance operating model: Data Owners and Stewards, decision rights, policy, standards, data classification and committees.

Data quality, lineage and platform

- Identify critical data elements,



define quality rules and thresholds, and set up monitoring, issue management and lineage.
- Assess the data platform (Snowflake, AWS, Power BI) for architecture, security, cost and environments; recommend a future state and remediation roadmap.

Analytics and AI readiness

- Map customer journeys and funnels; design reusable shared data sets for dashboards and reports.
- Assess AI readiness, rank automation and AI use cases, and set responsible AI and GenAI safety rules.

Delivery and operations

- Own the programme plan, RAID log, decision log, evidence repository and status reporting.
- Oversee the dashboard pipeline from BRD to UAT, Production and hypercare; unblock sign-offs with business owners.
- Guide the client EDO team on platform stability, incident and change processes, and the data request SOPs.

Handover and BAU

- Design BAU services, SOPs and service levels; train owners, stewards and the EDO team; lead handover acceptance and Go-Live readiness.

Required experience and qualifications

- 12–15+ years in data and analytics, including 5+ years leading data governance or data management programmes end to end.
- 5+ years in insurance or financial services; life insurance strongly preferred.
- Has set up a data governance operating model (owners, stewards, decision rights, committees) and taken it through executive approval.
- Has standardized KPIs across business units and built a KPI or business glossary used in production reporting.
- Has delivered a data quality programme with critical data elements, rules, thresholds and lineage.




- Has led a platform or architecture assessment and a remediation roadmap on a modern cloud data stack.
- Has handed a programme over to a BAU team, with SOPs, training and acceptance.
- Experience as a consultant or vendor lead working with client executives.
- Bachelor’s degree in computer science, information systems, statistics, business or a related field; a master’s degree is a plus.

Behavioural competencies

- Executive influence: gets decisions and sign-offs from senior leaders and busy business owners, and keeps approvals moving.
- Plain-language communication: turns frameworks into short material executives can read and act on.
- Facilitation: runs workshops where departments disagree, and brings them to one agreed definition.
- Pragmatism: balances valuable-practice governance with what a small team can actually run.
- Ownership: works without close supervision, and tracks commitments to closure.
- Coaching: builds capability in client teams so they can run the work after handover.

Preferred certifications

None is mandatory; proven delivery counts for more.

- CDMP (DAMA) or DCAM: data management
- PMP or PRINCE2: programme delivery
- SnowPro Core, or Microsoft Power BI Data Analyst: platforms
- ITIL 4 Foundation: BAU services
- An AI governance certification (for example IAPP AIGP): responsible AI

Success in the first 6 months

By

Measure

Month 1

Data Owners and Stewards named; access in place; plan, RAID and decision log running

Month 2

KPI, governance and data quality frameworks approved by the committees

Month 3

Platform roadmap approved; monthly data quality score live

Month 4

Growth blueprint and AI readiness plan approved

Month 5

Committee charter approved; handover items accepted by named owners

Month 6

Go-Live: BAU team runs the services without vendor support; Enterprise KPIs certified where a source exists

Work Location: In person

📌 Data Management & Governance Program Lead (RT Nagar)
🏢 Hival IT Solutions
📍 RT Nagar