Data Engineer, People Team
Builds a central HR 'People Data Middle Layer' in Microsoft Fabric for Changi Airport Group's People Team, engineering PySpark/Python pipelines and integrations from systems like SAP SuccessFactors and ServiceNow to power people analytics, governance, and Power BI self-service reporting.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Degree in Information Systems, Computer Science, Data Engineering, or a related field
- 4-8 years of dedicated data engineering experience with strong operational focus on Microsoft Azure and Microsoft Fabric data stacks
- Advanced proficiency in Python (PySpark) and T-SQL for data manipulation, semantic modelling, and business logic
- Experience navigating dynamic requirements, managing scope changes, and communicating trade-offs to non-technical stakeholders
- Ability to model and integrate disparate HR systems using varied ingestion methods (APIs, flat files, SFTP, connectors)
- Strict adherence to data privacy protocols when handling highly classified HR information
Nice to have
- Microsoft Certified: Azure Data Engineer Associate (DP-203) or Fabric Analytics Engineer (DP-600)
- Familiarity with HR/service APIs (SAP SuccessFactors, ServiceNow), Learning Management Systems (Cornerstone OnDemand), and workforce optimisation solutions
- Exposure to deploying LLMs, AI agents, or Azure OpenAI services over curated enterprise datasets
Full description
Changi Airport Group (CAG) is advancing its Digital Transformation within the People Team by building a highly scalable HR data infrastructure. As a Data Engineer, you will partner with the People Data Architect to construct a central “People Data Middle Layer” built natively within the Microsoft Fabric ecosystem. You will architect robust data pipelines, resolve complex system logic, and power advanced people analytics and AI initiatives in a fast-paced, evolving environment. This role sits within Changi Airport Group’s (CAG) human resource function and our mission is to attract and retain talents, build sustained capabilities and create an inspiring workplace
Key Responsibilities
- Engineer the People Data Middle Layer: Utilise Microsoft Fabric Lakehouse to consolidate various HR data sources. Drive heavy data transformations and build complex business logic primarily within Microsoft Fabric's scheduled pipelines and notebooks, leveraging PySpark/Python for efficient data ingestion, transformation, and distribution.
- Execute Diverse Data Integrations: Connect core HR platforms (SAP SuccessFactors, ServiceNow, Cornerstone OnDemand) using a hybrid approach. Build and secure direct APIs via Azure API Management (APIM) while managing alternative ingestion methods like flat file exports and custom connectors for systems without native API support.
- Domain-Specific Data Modelling: Solve highly specific, complex data mapping challenges, such as reconciling literal time values from scheduling systems with internal SAP SuccessFactors template codes. Apply deep domain knowledge of HR business rules to bridge significant data gaps and build reliable semantic models.
- Navigate Dynamic Project Scopes: Operate effectively within an agile environment where technical requirements and project scopes actively evolve. Engage directly with HR stakeholders to define requirements, negotiate deliverables under tight development runways, and continuously refine data solutions.
- Implement Data Governance: Establish automated data lineage, metadata management, and rigorous quality checks within Fabric to ensure structural integrity across HR systems.
- Enable Self-Service Analytics: Curate semantic layers and data marts within Microsoft Fabric to directly feed Power BI, enabling HR stakeholders to access clean datasets without bottlenecks.
- Ensure Security and Compliance: Enforce PDPA compliance and internal security policies using strict access controls and encryption for highly confidential data such as NRIC, salary, and performance ratings, including strategies for sensitive report protection and secure data handling during development.