Data Engineer, People Team
Posted Updated
Summary
A data engineer inside Changi Airport Group's HR (People) function who builds a 'People Data Middle Layer' on Microsoft Fabric — engineering PySpark pipelines, integrating HR systems like SAP SuccessFactors, ServiceNow and Cornerstone OnDemand, and delivering governed, Power BI-ready semantic datasets for people analytics and AI initiatives.
Job Title: Data Engineer (People Team) (30000031)
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. Key Requirements
Degree in Information Systems, Computer Science, Data Engineering, or a related field. 4 to 8 years of dedicated experience in data engineering, with a strong operational focus on Microsoft Azure and Microsoft Fabric data stacks. Advanced proficiency in Python (PySpark) and T-SQL for complex data manipulation, semantic data modelling, and business logic creation. Proven experience navigating dynamic engineering requirements, managing scope changes, and communicating technical trade-offs directly to non-technical stakeholders. Demonstrated ability to model and integrate highly disparate HR systems, utilising varied ingestion methods (APIs, flat files, SFTP, connectors). Strict adherence to data privacy protocols when handling highly classified HR information. Preferred Qualifications
Microsoft Certified: Azure Data Engineer Associate (DP-203) or Fabric Analytics Engineer (DP-600). Familiarity with core HR and service APIs (SAP SuccessFactors, ServiceNow, or equivalent systems), alongside Learning Management Systems (Cornerstone OnDemand, or equivalent systems) and workforce optimisation solutions. Exposure to deploying LLMs, AI agents, or Azure OpenAI services over curated enterprise datasets.
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. Key Requirements
Degree in Information Systems, Computer Science, Data Engineering, or a related field. 4 to 8 years of dedicated experience in data engineering, with a strong operational focus on Microsoft Azure and Microsoft Fabric data stacks. Advanced proficiency in Python (PySpark) and T-SQL for complex data manipulation, semantic data modelling, and business logic creation. Proven experience navigating dynamic engineering requirements, managing scope changes, and communicating technical trade-offs directly to non-technical stakeholders. Demonstrated ability to model and integrate highly disparate HR systems, utilising varied ingestion methods (APIs, flat files, SFTP, connectors). Strict adherence to data privacy protocols when handling highly classified HR information. Preferred Qualifications
Microsoft Certified: Azure Data Engineer Associate (DP-203) or Fabric Analytics Engineer (DP-600). Familiarity with core HR and service APIs (SAP SuccessFactors, ServiceNow, or equivalent systems), alongside Learning Management Systems (Cornerstone OnDemand, or equivalent systems) and workforce optimisation solutions. Exposure to deploying LLMs, AI agents, or Azure OpenAI services over curated enterprise datasets.