Job Summary:

The AVP, Data PlatformEngineering & SRE is responsible for building, operating, and continuouslyimproving SGX's enterprise data platform, ensuring it is scalable, reliable,secure, and efficient. The role combines data platform engineering, reliabilityengineering and operational excellence to deliver trusted data services thatsupport business growth, innovation, and operational resilience.

Working across cloud andon-premise environments, the incumbent will design and operate platformcapabilities that enable the delivery of high-quality data products, improve engineeringproductivity, strengthen observability, and enhance the reliability andresilience of SGX's data ecosystem. The role will leverage AI-assistedengineering practices and automation to reduce operational toil, improveservice reliability, accelerate delivery, and drive continuous improvementacross the platform lifecycle.

SGX Ambition & Career Path:

At SGX, technology is a core enabler ofgrowth, innovation, and trust. This role sits at the heart of that ambition byhelping to build advanced, scalable, and resilient data platforms that power asystemically important market infrastructure. The AVP, Data PlatformEngineering role will play a meaningful role in strengthening engineeringexcellence, delivering solutions that enhance performance, scalability and reliabilityacross 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.

Responsibilities:

Data Platform Engineering

• Design, build, and operate scalable data platform capabilities supporting batch, streaming, and API-based data services.
• Develop reusable platform services, frameworks, and engineering standards that accelerate delivery of data products.
• Build and maintain data platform infrastructure, including compute, storage, orchestration, and integration services.
• Partner with data engineers, architects, and business stakeholders to deliver platform capabilities aligned to business priorities.
• Drive platform modernisation initiatives across both cloud-native and on-premise environments.
• Establish platform capabilities that support data quality, lineage, monitoring, and governance requirements.

Reliability Engineering (SRE)

• Implement reliability engineering practices, service-level objectives (SLOs), monitoring standards, and operational governance across the data platform.
• Develop observability capabilities covering platform health, pipeline execution, service performance, data freshness, data completeness, and data quality.
• Improve platform resilience through automation, proactive monitoring, capacity management, and recovery testing.
• Lead incident investigation, root cause analysis, and continuous improvement initiatives.
• Identify opportunities for self-healing and operational automation to improve platform availability and reduce manual intervention.
• Implement controls and observability to ensure data accuracy, completeness, timeliness, and reliability.
• Support compliance, audit, risk management, and operational resilience objectives through robust platform controls.
• Explore AI-driven approaches for monitoring, incident detection, root cause analysis, anomaly detection, and operational automation.

Platform Automation & DevOps

• Build CI/CD pipelines and automated deployment processes to improve engineering productivity and release reliability.
• Implement Infrastructure-as-Code and platform automation practices.
• Develop reusable engineering tooling and automation frameworks that improve consistency, quality, and operational efficiency.
• Promote DevSecOps and engineering best practices across the platform lifecycle.
• Leverage AI-assisted development tools to improve engineering productivity and software quality.
• Drive adoption of engineering practices that improve delivery efficiency and reduce operational overhead.

Knowledge & Experience

. Experience: Provenexperiencebuilding and operating production grade data platforms incomplex enterprise environments. Strong troubleshooting and problem-solving skills in productionenvironments.

. Track record: Demonstratedability to deliver well-tested, maintainable software, contribute to codereviews and drive continuous improvement within a team.

. Technical stack: Strong hands-on skills with modern languages andframeworks such as Python or Java cloud platforms such as AWS, GCP or Azurecontainerisation and cloud-native services GitOps, CI/CD pipelines,infrastructure as code (terraform) and automated testing and observabilitytooling such as OpenTelemetry, Prometheus and Grafana proficiencyin Python, SQL, orchestrator and dbt/dataform (or equivalent) experience.

. Standards &environment: Solid understandingof security-by-design, resiliency patterns and operational excellence expectedin high-availability, regulated environments.

. Communication &leadership: Strong communicationand collaboration skills, with the ability to explain technical conceptsclearly and work effectively across cross-functional teams.

. Education &certifications: Bachelor's degree in Computer Science, Engineering, Informationand Communications Technology, or a related discipline.

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

Please note that the role may include production incidents response or deployment outside normal business hours including evenings, weekends, and public holidays, when required to ensure production services meet agreed availability and reliability targets.