Business Analysis with (Data Quality & Data & Technical Analysis)

Unison Group; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Unison Group is seeking a Data Quality Specialist to lead Data Quality Governance for strategic data and analytics initiatives. You will bridge business stakeholders with technical teams and drive the Data Quality Governance Framework, data quality requirements, and controls to ensure data is accurate and trustworthy for business use.

The role emphasizes collaboration with data engineers and analysts, driving data quality KPIs, and promoting governance across projects.

Qualifications

• Experience in data quality, governance, analytics or similar roles.
• Strong stakeholder engagement and facilitation skills.
• Translate business requirements into data quality needs.
• Strong analytical and problem-solving capabilities.
• Experience investigating data issues and root cause analysis.
• Excellent communication and documentation skills.

Responsibilities

• Lead implementation and adoption of the Data Quality Governance Framework.
• Define and maintain Data Quality rules, controls, standards, and processes.
• Engage stakeholders to understand data quality needs and requirements.
• Perform data analysis, profiling, validation, and root cause investigation.
• Identify, track, and drive resolution of data quality issues.
• Define and monitor Data Quality KPIs and reporting.
• Collaborate with delivery team to ensure correct DQ implementation.
• Support SIT, UAT, and production data validation activities.
• Promote Data Quality governance across the project.

Skills

Data quality

Data governance

Business analysis

Analytics

Stakeholder engagement

Power BI

Root cause analysis

Tools

SQL

Power BI

Job description

Role Overview

We are seeking a Data Quality Specialist to lead Data Quality Governance for strategic data and analytics initiatives. This role combines strong business analysis capabilities with data expertise to ensure data is accurate, trusted, and fit for business use.

The successful candidate will act as the bridge between business stakeholders and technical teams, driving the implementation of the Data Quality Governance Framework, defining data quality requirements, and ensuring effective data quality controls are established and maintained.

Key Responsibilities

• Lead the implementation and adoption of the Data Quality Governance Framework.
• Define and maintain Data Quality rules, controls, standards, and processes.
• Engage business stakeholders to understand data quality needs and business requirements.
• Perform data analysis, profiling, validation, and root cause investigation.
• Identify, track, and drive resolution of data quality issues.
• Define and monitor Data Quality KPIs and reporting.
• Collaborate with delivery team to ensure business logic and DQ requirements are correctly implemented.
• Support SIT, UAT, and production data validation activities.
• Promote Data Quality awareness and governance across the project.

Required Skills & Experience

• Experience in Data Quality, Data Governance, Business Analysis, Analytics, or similar roles.
• Strong stakeholder engagement and facilitation skills.
• Experience translating business requirements into data quality and data-related requirements.
• Strong analytical and problem-solving capabilities.
• Experience investigating data issues and performing root cause analysis.
• Ability to work effectively with both business and technical teams.
• Excellent communication and documentation skills.

Preferred Qualifications

• Experience with SQL for data analysis and validation.
• Understanding of data integration, ETL/ELT, and data pipelines.
• Experience with analytics and reporting platforms (e.g., Power BI).
• Familiarity with data governance, metadata, and data lineage concepts.

Ideal Candidate

• Speak confidently with business stakeholders.
• Challenge and clarify business rules and data definitions.
• Lead Data Quality Governance discussions and decisions.
• Work comfortably with Data Engineers and technical teams.
• Translate business needs into actionable data quality controls and requirements.