Data Management & Governance Program Lead

• *Data Management \& Governance Program Lead**

• *Role summary**

• *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

• *Reports to**

Engagement Director \- Capvirge; works day to day with the client’s Deputy CTO

• *Leads**

Project Manager, Project Coordinator, Data Governance Analyst, Data Quality \& Lineage Analyst, Business Analyst, Power BI Developers and Snowflake Data Engineer (with the client EDO team)

• *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.

The role also oversees delivery of the **16 tactical dashboards** (Power BI on Snowflake), from BRD and build to UAT sign\-off, Production and BAU.

• *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.

• *Team the role leads**

• *Role**

• *Focus**

• *Project Manager**

Programme plan, RAID log, action tracker and status reporting

• *Project Coordinator**

Meetings, follow\-ups, minutes and document control

• *Data Governance Analyst**

Data Owners and Stewards, business glossary, policies and standards (D2\)

• *Data Quality \& Lineage Analyst**

Data inventory, quality rules, monitoring and lineage (D3\)

• *Business Analyst (insurance)**

BRDs, KPI definitions and dashboard requirements (D1, D5\)

• *Power BI Developers**

Build, UAT and BAU support for the 16 dashboards

• *Snowflake Data Engineer**

Data models, pipelines and platform remediation (D4\)

• *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.

• *Technical and domain skills**

• *Area**

• *Must have**

• *Good to have**

• *Data governance**

DAMA\-DMBOK, federated operating models, RACI and decision rights, data classification

DCAM, data catalogue tools

• *KPIs and metrics**

KPI trees, SMART definitions, certification and change control

Management scorecards and target setting

• *Data quality and lineage**

Critical data elements, quality dimensions, rules and thresholds, issue management, column lineage

Automated quality checks in pipelines (Airflow), logical data models

• *Data platforms**

Snowflake, AWS (S3\), Power BI; environments, access control, cost (FinOps)

AWS Well\-Architected, TOGAF, privileged access (CyberArk)

• *Analytics**

Dashboard delivery lifecycle (BRD, UAT, hypercare), semantic models, shared data sets

Customer journey and funnel analytics

• *AI readiness**

Use\-case scoring; Predictive, Generative and Agentic AI concepts; responsible AI

NIST AI RMF, ISO/IEC 42001

• *Insurance domain**

Life and ILP products, persistency, APE, claims, IFRS 17 and statutory reporting, bancassurance and digital partners

Group insurance

• *Regulation (Philippines)**

Data Privacy Act (RA 10173\), Insurance Commission requirements, RA 11765 consumer protection

AML (RA 9160\)

• *Delivery and service**

Programme planning, RAID, gates, change control; BAU service design, SOPs, incident and change processes

ITIL, ADKAR change management

• *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 good\-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

Work Location: In person