Principal / Lead / Senior Data Engineer (Data Strategy)

Location: CAA-Changi Airport Terminal 2

Time Type: Full time

Job Description

[What the role is]

The Data Strategy section within CAAS' Data and Performance Division sets data policies, develops data infrastructure and architecture, and drives implementation strategies to enable data sharing across CAAS and the aviation ecosystem. It ensures the responsible use of data for policymaking, planning, operations, and R&D, while fostering a data-driven culture and promoting best practices to support long-term business goals.

[What you will be working on]

As a key member of the Data Strategy team, you will shape CAAS’ technical vision for data infrastructure. This role involves the designing of data scalable and interoperable data architecture that serves as the backbone for data sharing within CAAS and the wider aviation ecosystem. Working at the intersection of strategy and implementation, you will translate organisational and ecosystem data needs into scalable technical solutions, establish architectural standards, and guide the evolution of our data capabilities. You will design and maintain integrated solutions that enable seamless data access, sharing and innovation across the organisation and ecosystem partners. Alongside this strategic architecture work, you will build and operate critical end-to-end data pipelines, applying robust engineering practices to ensure data is ingested, transformed, validated and delivered securely and reliably. The ability to collaborate effectively with stakeholders will be key in driving alignment across teams and ensuring the success of these initiatives.

Key responsibilities include the following:

Data Architecture

• Design and develop enterprise data architecture that drives CAAS and ecosystem-wide strategic objectives
• Engage with CAAS’ business units and ecosystem partners to understand data requirements, translating these into cohesive technical architecture and roadmaps
• Establish scalable, secure and interoperable architectural standards aligned with WOG frameworks and aviation sector requirements
• Map and maintain comprehensive data flows across CAAS and ecosystem partners, ensuring consistency, lineage, and accessibility
• Develop reusable data models, services and architectural patterns that enable analytics, AI/ML and reporting use cases
• Evaluate and recommend emerging architectural approaches and technologies to enhance platform capabilities
• Document architecture, maintain data catalogue and metadata frameworks, and contribute to governance and compliance requirements
• Support change management and adoption of new architectural solutions, ensuring smooth integration with existing systems and aligning with business transformation efforts

Data Engineering

• Build and maintain end-to-end data pipelines covering ingestion, transformation, validation, orchestration and delivery
• Design and implement monitoring, automation and data quality frameworks to ensure accuracy, completeness, and reliability
• Optimise pipeline performance and troubleshoot data issues, implementing solutions to improve efficiency and scalability
• Collaborate with CAAS’ business units and ecosystem partners to understand requirements and iteratively refine pipelines to meet evolving analytical and operational needs
• Adopt and champion industry-standard data engineering practices to enhance trust and operational excellence
• Work with security team to put in place best security practices related to data pipelines, such as ensuring data is encrypted during transfer and storage, and that access control is enforced at the data layer

[What we are looking for]

• Trained in Computer Science, Engineering, Information Systems, or a related discipline
• 5 to 8 years of hands-on experience in data engineering, data architecture or platform development
• Proven hands-on expertise in building and optimising data pipelines and managing large-scale datasets 
• Strong knowledge of modern data platform solutions (e.g. Snowflake, Databricks) and cloud platforms (e.g. Azure, AWS)
• Experience with generative AI deployment, including LLM integration, prompt engineering or AI application development, would be an advantage
• Familiarity with data governance frameworks, metadata management and security / privacy requirements
• Strong problem-solving and analytical skills, with ability to bridge technical and business perspectives
• Excellent documentation and communication skills, with experience engaging diverse stakeholders across technical and non-technical audiences
• Collaborative mindset with demonstrated ability to work effectively across organisational boundaries and align cross-functional teams

Note: Your appointment designation will commensurate with your relevant work experience. Successful candidates will be offered a 3-year contract in the first instance and may be considered for placement on a permanent tenure or subsequent contract renewal.