Job Description

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Role Purpose
The Programme Manager will lead the end-to-end setup, mobilisation, and execution of the enterprise-wide Client Data Quality & Data Governance Programme.
They will orchestrate the analysis of client data quality issues across the entire lifecycle, define, apply and mature the Data Quality Root Cause Assessment (RCA) Framework, define and sequence workstreams, coordinate multi-team delivery, and drive the organisation toward sustainable, long-term client data quality improvements.
This role serves as the central integrator across people, process, technology, governance, and architecture domains.
Requirements
Core Responsibilities
1. Programme Mobilisation & Governance Setup
Establish the full programme construct, including:

• Programme Working Group

• Programme Steering Committee

• Stakeholder map (cross-platform, cross-process, cross-team)

Develop programme governance artefacts:

• Integrated programme plan & critical path

• RAID logs

• Resource model & allocation map

• Reporting templates and programme dashboards

Secure alignment on scope, objectives, and operating rhythms.
2. Lead the End-to-End Diagnostic & Root Cause Assessment
Oversee the application of the Data Quality Root Cause Assessment (DQ RCA) Framework across:

• Client onboarding platforms

• Client maintenance platforms

• Operating model & processes

• System-to-system integrations

• Target platforms and architectural constraints

• Data governance dimensions (lineage, stewardship, standards, KPIs)

Ensure RCA analysis captures:

• People, process, technology and governance issues

• Cause-effect relationships

• Both issues and stakeholder requirements

Consolidate findings into a unified diagnostic and prioritisation matrix.
3. Define the Programme Roadmap & Workstreams
Build a comprehensive roadmap covering 12-18 months.
Define discrete workstreams for:

• Process redesign

• Platform remediation & enhancements

• Data integration fixes

• Operating model & responsibility shifts

• Governance enablement

• Architectural transition states

Sequence initiatives based on:

• Dependencies

• Organisational capacity

• Critical path

• Business risk & regulatory imperatives

4. Coordinate Distributed Delivery Across All Teams
Work closely with:
CDM Team

• Technology platform teams (CDX, D365, PCCA, Everest, iMeta etc.)

• PLC operational teams

• Data Governance

• Architects

Manage and align cross-team backlogs, ensuring all client-data-related changes are delivered consistently.
Facilitate solution design workshops and ensure joint ownership of fixes across business and technology.
5. Architecture Alignment & Transition State Planning
Partner with architects to map:

• AS-IS architecture

• TO-BE architecture

• All transitional states

Ensure alignment between RCA outputs and required architecture changes.
Oversee integration remediation, data flow redesign, and platform consolidation considerations.
6. Stakeholder Engagement & Communication
Own communication strategy across senior executives, delivery teams, data governance, and operations.
Establish routines:

• Steering packs

• Working Group sessions

• Issue escalation flows

• Cross-platform alignment forums

Build shared understanding of client data challenges across all stakeholders.
7. Benefits Realisation & Sustainability
Define measurable data quality KPIs and target improvements.
Ensure solutions are sustainable and embedded in:

• Operating model changes

• Governance structures

• Training and stewardship models

• Platform standards and controls

Build a long-term mechanism for continuous DQ monitoring and feedback loops
Required Skills & Experience
Programme Leadership

• Proven experience delivering large-scale, multi-year enterprise programmes (data governance, regulatory, or architecture-heavy preferable).

• Demonstrated ability to operate in complex matrix environments with distributed delivery responsibility.

Client Data & Data Governance Expertise

• Deep knowledge of:

Data lineage, ownership, stewardship * Data standards & quality controls

• Root cause assessment methodologies

• Master data & reference data management

Understanding of regulatory obligations (e.g., GDPR over-retention).
Technical & Architectural Acumen

• Familiarity with system integration, data flows, and platform architecture.

• Ability to translate RCA findings into architectural and technical change.

Process & Operating Model Design

• Experience modernising or redesigning business processes and roles.

• Comfortable defining new accountability models and embedding them.

Stakeholder Management

• Strong senior-level engagement experience (Exec sponsors, COO, CIO, Heads of Ops/Tech).

• Skilled facilitator capable of driving consensus.

Change & Communication

• Skilled in aligning diverse teams around a common vision.

• Experienced in developing structured programme communication strategies.

Key Deliverables
Programme Setup

• Programme charter, scope & objectives

• Stakeholder map

• Governance model (SteerCo, Working Group, cadence)

• Integrated programme plan (18-24 months)

Diagnostic Phase

• Comprehensive RCA assessment (across all dimensions)

• Prioritised root cause library

• Integrated issue + requirement catalogue

• End-to-end AS-IS process and system maps

Design & Roadmap

• TO-BE architecture & operating model

• Transition state definitions

• Sequenced workstreams, initiatives, and critical path

• Resource & capacity model

Execution

• Monthly SteerCo packs

• Weekly Working Group updates

• RAID management

• Progress reporting against KPIs

• Benefits realisation plan

Success Measures

• Clear, organisation-wide understanding of client data lifecycle issues.

• RCA completed comprehensively, with validated root causes across all platforms.

• A fully mobilised and functioning delivery construct (SteerCo + WG + distributed teams).

• A sequenced programme delivering measurable reduction in data quality issues.

• Embedded sustainable solutions across people, process, technology, and governance.

Skills Required