Data Engineer

Key Responsibilities

• Build and maintain data pipelines from the HRIS platform, attendance devices, and payroll returns into a governed HR data store.
• Design and maintain HR data models supporting cross-BU reporting despite differing structures and employment types.
• Own data quality engineering: automated validation rules, anomaly detection, reconciliation checks, and audit trails.
• Build the self-service reporting layer: curated datasets and semantic models so BU HR can answer routine questions without filing requests.
• Standardize HR metric definitions across 5 BUs in the data layer (one definition of headcount, turnover, absence).
• Support statutory, manpower, and audit reporting extracts.
• Apply access controls and masking — this role handles salary and personal data at source.

Requirements

• Bachelor's in Computer Science, Information Systems, or related field.
• 3–6 years in data engineering; strong SQL and Python.
• ETL/ELT tooling and orchestration (Airflow, dbt, or equivalent); warehouse or lakehouse experience.
• Data modeling for analytics (dimensional modeling); BI tool integration (Power BI, Tableau, or Looker).
• Data quality engineering and pipeline observability.
• High confidentiality discipline, experience with PII handling, masking, and access control.