G11 - Data Engineer

Job Purpose

The Data Engineer will be responsible for designing, developing, and maintaining data pipelines and models to support Finance reporting and analytics. The role ensures data integrity, security, and compliance with standards while enabling downstream business intelligence and emerging AI capabilities.

Key Responsibilities

Data Integration and Pipeline Development

• Design, implement, and operate ETL/ELT processes to ingest data from enterprise systems, including Workday RAAS, into the data platform.
• Collaborate with system owners to extract and consolidate report data from multiple platforms.

Data Modeling and Optimization

• Develop well-documented and efficient data models to support Finance reporting requirements.
• Ensure scalability and performance for analytics workloads.

Data Quality

• Implement data validation, observability, and lineage tracking.
• Enforce compliance with PDPA and internal security policies.

Automation And Orchestration

• Develop automated workflows and transformation processes using CI/CD principles.
• Contribute to infrastructure-as-code practices for deployment consistency.

Business Intelligence Enablement

• Partner with Finance analysts to provision curated data sets for dashboards and reporting.
• Optimize SQL queries for performance and reliability.

Ai/Ml Support (Optional)

• Prepare datasets and features for AI/ML use cases.
• Collaborate with data science teams on model deployment and evaluation.

Documentation And Collaboration

• Produce technical documentation, including runbooks and design records.
• Work closely with Finance stakeholders to align solutions with business needs.

Requirements

Essential

• Proficiency in SQL and Python for data processing and automation.
• Experience in ETL/ELT pipeline development and data modeling.
• Knowledge of data quality, observability, and practices.
• Familiarity with enterprise systems integration (Workday RAAS experience preferred).
• Understanding of CI/CD principles and version control tools.
• Strong communication and documentation skills.

Desirable

• Exposure to BI tools such as Tableau or Power BI.
• Experience with cloud data platforms (Azure, AWS, or GCP).
• Familiarity with data orchestration frameworks and infrastructure automation.
• Knowledge of AI/ML enablement and data frameworks.

Performance Indicators

• Timely delivery of reliable data pipelines and models.
• Compliance with data security and standards.
• High data quality and availability for Finance reporting and analytics.
• Effective collaboration with stakeholders and clear documentation.