Role Purpose
Act as the Senior Technical Subject Matter Expert (SME) and trusted advisor to project leadership across Data Quality, Data Readiness, and Data Modelling.
The SME will work closely with project leadership to shape technical positions, challenge project outputs, resolve complex data-related issues, and support preparation for key client discussions, workshops, and decision points.
The role requires strong technical depth, strategic thinking, and the ability to translate complex data challenges into clear, defensible recommendations for senior stakeholders and clients.
Key Responsibilities
-
Advise project leadership on complex Data Quality, Data Readiness, and Data Modelling topics ahead of client meetings, workshops, steering discussions, and major submissions.
-
Provide expert guidance on:
- Data profiling
- Critical Data Element (CDE) identification
- Data Quality dimensions
- DQ rule design and applicability
- Thresholds and scoring methodologies
- Exceptions and exclusions
- Root cause analysis
- Remediation strategies
-
Provide senior-level review and challenge of Conceptual, Logical, and Physical Data Models, including:
- Modelling approach and standards
- Entity and attribute design
- Relationships and cardinality
- Primary and foreign keys
- Normalization
- Data types
- Naming conventions
- Alignment with business requirements
-
Assess consistency and alignment across data models, source systems, CDE definitions, DQ rules, and target data architecture, identifying structural or design issues that may impact data quality, data readiness, or downstream delivery.
-
Provide expert guidance on complex scenarios involving:
- Poor or incomplete source data
- Unavailable or unreliable attributes
- Data modelling limitations
- Upstream system dependencies
- Business or technical constraints
-
Determine and advise on the appropriate treatment of complex issues, including whether they require remediation, exception, model change, scope adjustment, or methodology change.
-
Challenge the team's methodology, assumptions, technical approach, and conclusions before they are presented to the client.
-
Help project leadership formulate clear, technically sound, and defensible positions for client discussions and decision-making.
-
Connect profiling results, data models, CDEs, DQ rules, execution results, scores, root causes, and remediation activities to provide a holistic view of overall Data Readiness.
-
Identify systemic or structural data issues that may have broader implications across workstreams, systems, or downstream processes.
-
Participate selectively in critical client meetings, workshops, and technical discussions, providing senior-level technical guidance when required.
-
Provide rapid expert assessment and recommendations when client challenges, escalations, or complex technical issues arise.
Key Skills & Experience
- Significant experience in Data Quality, Data Governance, Data Readiness, and Data Modelling.
- Strong hands-on expertise in Conceptual, Logical, and Physical Data Modelling.
- Deep understanding of data profiling, CDEs, DQ dimensions, rule design, scoring methodologies, thresholds, exceptions, and remediation.
- Strong understanding of relational data structures, normalization, keys, relationships, and data architecture.
- Ability to assess the impact of source-system limitations and upstream dependencies on data quality and readiness.
- Strong experience in technical review, challenge, and quality assurance of data deliverables.
- Ability to translate complex technical issues into clear recommendations for senior leadership and client stakeholders.
- Strong analytical and problem-solving capabilities with the ability to make sound decisions in ambiguous situations.
- Excellent stakeholder management and communication skills.
- Experience working in large-scale consulting, data transformation, data governance, or enterprise data programmes is highly preferred.
Key Competencies
- Data Quality & Data Governance
- Data Modelling & Architecture
- Data Readiness Assessment
- Technical SME Leadership
- Methodology & Technical Challenge
- Root Cause Analysis
- Problem Solving & Decision Making
- Client Advisory & Stakeholder Management
- Strategic Thinking
- Executive Communication
Role Outcome
The successful candidate will provide senior technical assurance and advisory support to project leadership, ensuring that key data-related positions, methodologies, models, and conclusions are technically robust, commercially defensible, and ready for client discussion and decision-making.
