AVP, Software Engineer (Data)

Singapore Exchange Limited; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Singapore Exchange Limited is seeking software and data engineers to design, build and operate scalable data products and platforms. The role covers production-ready applications, data pipelines (batch/streaming), automated testing, secure development, and governance across trading, risk and enterprise systems.

You'll contribute to CI/CD, IaC, and incident response, while mentoring juniors and advancing agentic AI capabilities within the SDLC to enhance delivery speed and quality.

Responsibilities

• Independently design, develop and deliver production-ready applications, services and APIs with appropriate quality and security controls, including the user-facing products that extend the data platform, data-as-a-service services and data agents etc.
• Design scalable system and data components and participate in architectural decisions, spanning application, API, storage, processing and data serving layers.
• Design, build and operate data products — curated, documented, contract-backed datasets and data services — that consumers across the organisation and beyond can discover, trust and use without needing to understand the upstream systems.
• Build and extend shared data platform capabilities spanning ingestion, storage, processing, orchestration, cataloguing and self-service tooling, so teams across SGX Group can deliver data capabilities safely and at speed.
• Independently design, develop and deliver production-ready batch and streaming pipelines with appropriate quality, performance and security controls.
• Design and maintain automated tests, validation, reconciliation and anomaly detection for both applications and data, and own service levels for freshness, completeness and accuracy.
• Deliver software and pipelines that comply with secure development standards and handle sensitive market, client and reference data appropriately.
• Implement lineage, cataloguing, entitlements, access control, retention and privacy controls in line with regulatory and internal governance obligations, and surface them through the tooling that data users interact with.
• Independently develop and support integrations between the data platform and trading, clearing, data services, market operations, risk and enterprise systems.
• Deliver solutions through standardised CI/CD pipelines, infrastructure as code and engineering workflows, applying the same engineering rigour to data assets as to application code.
• Maintain operational ownership of the applications, pipelines and data services you build, and contribute to production reliability, including incident response.
• Improve productivity through automation of repetitive engineering and data operations work, including self-service capabilities that reduce manual handling of data requests.
• Mentor junior engineers and contribute to team capability uplift across software and data engineering practice.
• Apply agentic AI across the SDLC to deliver features faster and with better quality, including using agents for requirements clarification, application and transformation code generation, test and data-quality rule creation, code review preparation, documentation, lineage mapping and defect analysis, while retaining accountability for correctness, security and production readiness. Build and curate the governed data foundations that make analytics and AI workloads viable.
• Collaborate effectively with product, architecture, infrastructure, data governance, analytics and delivery stakeholders, as well as internal and external data consumers, to translate complex requirements into practical, high-quality engineering solutions.

Job description

• Software Development: Independently design, develop and deliver production-ready applications, services and APIs with appropriate quality and security controls, including the user-facing products that extend the data platform, data-as-a-service services and data agents etc.
• Software Design: Design scalable system and data components and participate in architectural decisions, spanning application, API, storage, processing and data serving layers.
• Data Product Engineering: Design, build and operate data products — curated, documented, contract-backed datasets and data services — that consumers across the organisation and beyond can discover, trust and use without needing to understand the upstream systems.
• Data Platform Engineering: Build and extend shared data platform capabilities spanning ingestion, storage, processing, orchestration, cataloguing and self-service tooling, so teams across SGX Group can deliver data capabilities safely and at speed.
• Data Pipeline Development: Independently design, develop and deliver production-ready batch and streaming pipelines with appropriate quality, performance and security controls.
• Data Quality & Reliability: Design and maintain automated tests, validation, reconciliation and anomaly detection for both applications and data, and own service levels for freshness, completeness and accuracy.
• Secure Software & Data Development: Deliver software and pipelines that comply with secure development standards and handle sensitive market, client and reference data appropriately.
• Data Governance & Compliance: Implement lineage, cataloguing, entitlements, access control, retention and privacy controls in line with regulatory and internal governance obligations, and surface them through the tooling that data users interact with.
• System & Data Integration: Independently develop and support integrations between the data platform and trading, clearing, data services, market operations, risk and enterprise systems.
• SDLC & Delivery Excellence: Deliver solutions through standardised CI/CD pipelines, infrastructure as code and engineering workflows, applying the same engineering rigour to data assets as to application code.
• Observability & Production Support: Maintain operational ownership of the applications, pipelines and data services you build, and contribute to production reliability, including incident response.
• Automation & Productivity: Improve productivity through automation of repetitive engineering and data operations work, including self-service capabilities that reduce manual handling of data requests.
• Leadership & Mentoring: Mentor junior engineers and contribute to team capability uplift across software and data engineering practice.
• Agentic AI Engineering: Apply agentic AI across the SDLC to deliver features faster and with better quality, including using agents for requirements clarification, application and transformation code generation, test and data-quality rule creation, code review preparation, documentation, lineage mapping and defect analysis, while retaining accountability for correctness, security and production readiness. Build and curate the governed data foundations that make analytics and AI workloads viable.
• Collaborate effectively with product, architecture, infrastructure, data governance, analytics and delivery stakeholders, as well as internal and external data consumers, to translate complex requirements into practical, high-quality engineering solutions.