Data Modelling Lead (m/f/d)

Halian; Abu Dhabi; On-site; AED 300,000 - 600,000; Full time

Job summary

Halian is seeking a Senior Technical SME to act as a trusted advisor to project leadership across Data Quality, Data Readiness, and Data Modelling. The role shapes technical positions, challenges outputs, and supports client discussions with clear, defensible recommendations.

Work involves senior-level review of data models, profiling, CDE design, DQ rules, and remediation strategies, ensuring alignment with business requirements and data architecture.

Qualifications

• Significant experience in Data Quality, Data Governance, Data Readiness, and Data Modelling.
• Strong hands-on expertise in Conceptual, Logical, and Physical Data Models.
• Excellent stakeholder management and communication skills.

Responsibilities

• Advise project leadership on Data Quality, Data Readiness, and Data Modelling topics ahead of client meetings.
• Provide expert guidance on data profiling, CDE identification, DQ dimensions, rule design, scoring methodologies, thresholds, exceptions, and remediation.
• Provide senior-level review of Conceptual, Logical, and Physical Data Models.
• Assess consistency across data models, source systems, CDE definitions, DQ rules, and target data architecture.
• Challenge the team’s methodology, assumptions, and conclusions before client presentations.
• Help leadership formulate clear, technically sound positions for client discussions.
• Connect profiling results, data models, CDEs, DQ rules, and remediation to show holistic Data Readiness.
• Identify systemic data issues with broader implications across workstreams.
• Participate in critical client meetings, workshops, and technical discussions.
• Provide rapid expert assessment during client challenges or escalations.

Skills

Data Quality

Data Governance

Data Modelling

Data Readiness

Stakeholder Management

Executive Communication

Job description

Role Purpose

Act as theSenior Technical Subject Matter Expert (SME)and trusted advisor to project leadership acrossData 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 intoclear, defensible recommendations for senior stakeholders and clients.

Key Responsibilities

• Advise project leadership on complexData Quality, Data Readiness, and Data Modellingtopics 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 ofConceptual, 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 acrossdata 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 requireremediation, exception, model change, scope adjustment, or methodology change.

• Challenge the team'smethodology, assumptions, technical approach, and conclusionsbefore they are presented to the client.

• Help project leadership formulateclear, technically sound, and defensible positionsfor client discussions and decision-making.

• Connect profiling results, data models, CDEs, DQ rules, execution results, scores, root causes, and remediation activities to provide aholistic view of overall Data Readiness.

• Identify systemic or structural data issues that may have broader implications across workstreams, systems, or downstream processes.

• Participate selectively incritical client meetings, workshops, and technical discussions, providing senior-level technical guidance when required.

• Provide rapid expert assessment and recommendations whenclient challenges, escalations, or complex technical issuesarise.

Key Skills & Experience

• Significant experience inData Quality, Data Governance, Data Readiness, and Data Modelling.
• Strong hands‑on expertise inConceptual, Logical, and
• Deep understanding ofdata profiling, CDEs, DQ dimensions, rule design, scoring methodologies, thresholds, exceptions, and remediation.
• Strong understanding ofrelational 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 intechnical review, challenge, and quality assurance of data deliverables.
• Ability to translate complex technical issues into clear recommendations forsenior 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 inlarge-scale consulting, data transformation, data governance, or enterprise data programmesis 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 providesenior technical assurance and advisory supportto 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.