About The Role

As a Data Quality Officer for HR & Reference Data, you will be the key enabler in maximizing the value and trustworthiness of our most critical enterprise domains: our workforce information and core reference datasets.

You will act as a proactive partner, collaborating closely with business and technical teams. A critical part of your role is bridging perspectives—from HR business partners to IT architects—into clear, actionable data analysis.

Your mission is to resolve data issues and nurture a proactive prevention mindset across the organization. You will translate HR processes and Reference Data requirements into formal data quality policies, rules, and governance standards. By storylining data health metrics and serving as a data provocateur when needed, you will drive the continuous improvement of our core data foundation.

Key Responsibilities

Domain-Specific Insight Generation & Profiling:

Perform deep-dive root cause analysis on HR datasets (e.g., employee lifecycle, payroll interfaces, org structures) and Reference Data (e.g., enterprise code tables, locations, job classifications, cost centers) to isolate systemic, process, or integration issues.
Conduct thorough data profiling on critical master and reference datasets to detect anomalies, cross-system discrepancies, orphan records, and data drift.
Document findings and quantify the business impact of poor data quality on operational HR, compliance, reporting, and downstream integrations.

Stakeholder Collaboration & Standard Setting:

Work closely with HR Data Stewards, Data Governance, and IT to define, document, and enforce clear data quality rules and reference data standards.
Translate HR business rules and Reference Data governance policies into precise technical specifications for automated validation and monitoring tools.
Act as the primary liaison between business domain owners and technical teams, ensuring alignment on data lineage and data definitions.

Monitoring, Reporting & Governance:

Maintain domain-specific Data Quality Dashboards (e.g., tracking HR data completeness, reference data synchronization) for clear visibility across business units.
Track and report HR and Reference Data quality KPIs to leadership, driving transparency and accountability.
Support reference data management processes, ensuring code values, mappings, and taxonomies remain synchronized across target applications.

Remediation & Prevention:

Collaborate with IT and HR Tech teams to define requirements for data cleansing, automated enrichment, and exception management.
Support business teams at the point of data entry/creation to improve source data quality and minimize manual workarounds.

Your Profile

Boundary Spanner: Ability to connect HR business processes and enterprise reference data structures with backend technical architectures.
Influencer & Storyteller: Skilled at translating complex data anomalies into compelling narratives for HR leadership and business managers.
Collaborator: A strong team player dedicated to building cross-functional alignment across HR Operations, Enterprise Data Management/Governance, and IT.
Mindset: Detail-oriented, persistent, and proactive about driving data transparency and operational excellence.

Qualifications

Bachelor's or Master's degree in Information Systems, Computer Science, Statistics, HR Analytics, or a related field.
3+ years of experience as a Data Quality Officer, Data Governance Analyst, or Data Steward, with direct experience handling HR data, Master Data Management (MDM), or Reference Data domains.
Essential: Strong proficiency in SQL for complex data querying, profiling, and joining datasets across multi-table environments.
Hands-on experience with modern HR Information Systems (e.g., Workday, SAP SuccessFactors, Oracle HCM) and Reference Data concepts (code lists, hierarchies, mapping tables).
Fluent in English with excellent verbal and written communication skills to interact effectively with global teams.

Preferred Skills

Familiarity with Data Governance frameworks (Metadata Management, Data Lineage, Data Cataloging).
Experience using scripting languages (e.g., Python) for automated data checks or profiling is a plus.
Knowledge of global HR data privacy standards (e.g., GDPR, local DPDP regulations).