Data Quality Lead (m/f/d)

Halian; Abu Dhabi; On-site; AED 335,000 - 513,000; Full time

Job summary

Halian is seeking a seasoned QA and delivery assurance expert in Abu Dhabi to own end-to-end quality for Data Quality, Readiness, and Modelling deliverables before client submission. The role acts as the final internal quality gate, ensuring accuracy, completeness, traceability, and alignment with project methodology and client acceptance criteria.

Strong data quality, governance, and modelling background is essential.

Qualifications

• Strong experience in Data Quality Assurance, Data Governance, and Data Modelling.
• Hands-on understanding of Conceptual, Logical, and Physical Data Models.
• Knowledge of data profiling, CDEs, DQ dimensions, rules, scoring, and remediation.

Responsibilities

• Independently QA the complete client submission package, including data profiling outputs, CDE scope, data quality rulebooks, dashboards and reports, and remediation trackers.
• Perform detailed QA of data modelling deliverables at conceptual, logical, and physical levels.
• Validate entities, attributes, relationships, keys, naming conventions, data types, and model documentation.
• Validate alignment between data models and downstream Data Quality deliverables, ensuring consistency across tables, CDEs, keys, and business definitions.
• Conduct cross-deliverable reconciliation to identify inconsistencies across scope, rule IDs, CDEs, data quality dimensions, and scores.
• Independently reproduce or validate critical Data Quality calculations and ensure traceability to evidence and methodology.
• Review exclusions, low-coverage areas, and source-system limitations with documented rationale and impact.
• Maintain a QA checklist and issue register, classify findings by severity and risk, and drive resolution with stakeholders.
• Prepare final readiness recommendations: Ready / Not Ready for Client Submission.

Skills

Data Quality Assurance

Data Governance

Data Modelling

QA Processes

SQL Validation

Tools

SQL

Job description

Role Purpose

Own the independent, end-to-endQuality Assurance (QA) and delivery assuranceof Data Quality, Data Readiness, and Data Modelling deliverables before submission to the client.

The role will act as thefinal internal quality gate, ensuring that all deliverables are accurate, complete, consistent, traceable, and aligned with the agreed project methodology, architecture, dependencies, business requirements, and client acceptance criteria.

The ideal candidate should have strong experience inData Quality, Data Modelling, Data Governance, and QA, with the ability to independently review complex deliverables and identify cross-functional inconsistencies before client submission.

Key Responsibilities

• Independently QA the complete client submission package, including:

  • Data profiling outputs
  • Critical Data Element (CDE) scope
  • Data Quality rulebooks
  • Bronze and Silver execution logs
  • Failed records
  • Data Quality scores
  • Dashboards and reports
  • Annexes and supporting documentation
  • Remediation trackers
  • Closure reports and supporting evidence

• Perform detailed QA ofdata modelling deliverables, including conceptual, logical, and physical data models.

• Validate data model components such as:

  • Entities and attributes
  • Relationships and cardinalities
  • Primary and foreign keys
  • Naming conventions and standards
  • Data types
  • Model documentation

• Validate alignment betweendata models and downstream Data Quality deliverables, ensuring consistency across tables, entities, attributes, CDEs, keys, and business definitions.

• Performcross-deliverable reconciliationto identify inconsistencies or mismatches across:

  • Scope
  • Rule IDs
  • CDEs
  • Data Quality dimensions
  • Rule counts
  • Execution results
  • Failed records
  • DQ scores
  • Timestamps
  • Remediation status
  • Dashboard reporting

• Independently reproduce or validatecritical Data Quality calculationsand ensure that reported Bronze and Silver scores are fully traceable to the underlying execution evidence and agreed methodology.

• Validate completeness of deliverables against agreedclient requirements, project scope, and acceptance criteria, including coverage of tables, CDEs, models, DQ dimensions, rules, evidence, and required documentation.

• Reviewexclusions, exceptions, low-coverage areas, and source-system limitations, ensuring that appropriate rationale, impact assessment, and supporting evidence are documented.

• Maintain a structuredQA checklist and issue register, ensuring all findings are properly documented and tracked through closure.

• Classify QA findings based onseverity, business impact, and client submission risk.

• Work closely with Data Quality, Data Modelling, Data Governance, and other workstream teams to drive timely resolution of identified issues.

• Conduct final readiness reviews and provide a clear“Ready / Not Ready for Client Submission”recommendation.

Key Skills & Experience

• Strong experience inData Quality Assurance, Data Governance, Data Modelling, or Data QA.
• Hands-on understanding ofConceptual, Logical, and Physical Data Models.
• Strong knowledge ofdata profiling, CDEs, DQ dimensions, DQ rules, scoring, and remediation processes.
• Experience performingcross-functional and cross-deliverable reconciliation.
• Strong SQL skills for data validation and independent verification of DQ results.
• Ability to trace reported metrics and scores back to underlying execution evidence.
• Strong understanding ofrelational databases, primary/foreign keys, relationships, cardinality, and data structures.
• Experience working with large and complex data transformation or data quality projects.
• Strong attention to detail with an ability to identify inconsistencies across multiple deliverables.
• Excellent analytical, problem-solving, documentation, and stakeholder management skills.
• Ability to work independently and confidently challenge deliverables before client submission.
• Experience working in consulting or client-facing environments is preferred.

Key Competencies

• Data Quality & Data Governance
• Data Modelling
• QA & Delivery Assurance
• SQL & Data Validation
• Cross-Deliverable Reconciliation
• Root Cause Analysis
• Issue & Risk Management
• Attention to Detail
• Stakeholder Management
• Client Delivery Readiness

Role Outcome

The successful candidate will ensure thatonly complete, accurate, consistent, evidence-backed, and client-ready deliverablesare submitted, minimizing quality issues, inconsistencies, and rework during client review.