Assistant Vice President

Job Summary

The AVP, Software Engineer (Data) is responsible for designing, developing, and supporting scalable software solutions, APIs, and reusable services that power SGX's enterprise data ecosystem. Working closely with Data Engineers, Platform Engineers, and Architects, the role delivers high-quality engineering solutions that enable trusted data products, self-service data access, and business capabilities across the organisation.

The successful candidate will apply modern software engineering practices, cloud-native technologies, automation, and AI-assisted development tools to improve platform capabilities, engineering productivity, and operational resilience.

SGX Ambition & Career Path:

At SGX, technology is a core enabler of growth, innovation, and trust. This role sits at the heart of that ambition by helping to build advanced, scalable, and resilient  software solutions for data that power a systemically important market infrastructure. The AVP, Software Engineer (Data) role will play a meaningful role in strengthening engineering excellence, delivering solutions that enhance performance, scalability and reliability across a fast-evolving financial markets landscape.

For candidates with strong ambition, this role offers a compelling platform for growth. It provides the opportunity to deepen technical mastery across modern engineering, cloud, platform services, and operational resilience, while expanding influence across architecture, product delivery, and enterprise transformation initiatives. Over time, the role can evolve along multiple pathways, including senior individual contributor tracks such as Lead Engineer, Principal Engineer, or Architect, as well as broader leadership opportunities in engineering management, platform leadership, or strategic technology delivery. For professionals who want to combine hands-on engineering with visible impact, SGX offers both the scale and significance to build a rewarding long-term career.

Job Responsibilities

Software Engineering for Data Ecosystems

• Software Development: Independently design, develop and deliver production-ready software with appropriate quality and security controls for data ecosystems.


• Software Design: Design scalable system components and participate in architectural decisions.


• API capabilities: Develop secure, scalable, and well-documented APIs to enable Data-as-a-Service capabilities. Support self-service data access capabilities through APIs, applications, and platform services, improving accessibility and usability of enterprise data assets.


• Secure Software Development: Deliver software that complies with secure development standards.


• Testing & Quality Engineering: Design and maintain automated tests to ensure quality and resilience.


• System Integration: Independently develop and support integrations between platforms and systems.


• SDLC & Delivery Excellence: Deliver solutions through standardised CI/CD pipelines and engineering workflows.


• Observability & Production Support: Maintain operational ownership of services and contribute to production reliability.


• Automation & Productivity: Improve productivity through automation of repetitive engineering work.


• Leadership & Mentoring: Mentor junior engineers and contribute to team capability uplift.


• Agentic AI Engineering: Apply agentic AI across the SDLC to deliver features faster and with better quality, including using agents for requirements clarification, code generation, unit test creation, code review preparation, documentation and defect analysis, while retaining accountability for correctness, security and production readiness.


• Collaborate effectively with product, architecture, infrastructure, and delivery stakeholders to translate complex requirements into practical, high-quality engineering solutions.

Job Requirements

• Experience: Proven experience building and supporting production-grade applications across front-end, back-end, APIs and data platform services in complex enterprise environments.


• Track record: Demonstrated ability to deliver well-tested, maintainable software, contribute to code reviews and drive continuous improvement within a team.


• Technical stack: Strong hands-on skills with modern languages and frameworks such as Python, Java, Go or TypeScript; cloud platforms such as AWS, GCP or Azure; containerisation and cloud-native services; GitOps, CI/CD pipelines, infrastructure as code and automated testing; and observability tooling such as OpenTelemetry, Prometheus and Grafana.


• Standards & environment: Solid understanding of security-by-design, resiliency patterns and operational excellence expected in high-availability, regulated environments.


• Communication & leadership: Strong communication and collaboration skills, with the ability to explain technical concepts clearly and work effectively across cross-functional teams.


• Education & certifications: Bachelor’s degree in Computer Science, Engineering, Information and Communications Technology, or a related discipline.


• Domain Knowledge (Good to Have): Exposure to financial market infrastructure, including securities and derivatives trading, clearing, settlement, market operations, or exchange-related systems.