Top Data & Analytics Jobs in Singapore

Build scalable batch and real-time ETL pipelines, data models, and data products for Airwallex’s Customer Data Platform. Develop trusted data foundations across warehouses and cloud infrastructure to support analytics, machine learning, operational decision-making, business intelligence, and AI applications. Partner with globally distributed teams on complex technical work and apply data engineering best practices.

Build scalable batch and streaming ETL pipelines for Airwallex’s Customer Data Platform. Design data foundations, schemas, and models across databases and warehouses to support business intelligence, machine learning, operational decisions, and AI applications. Partner with globally distributed teams on complex technical projects while applying strong problem-solving and collaboration skills.

Designs and owns scalable batch and streaming data pipelines, data models, and infrastructure for business and AI use cases. Partners with engineering and cross-functional teams to deliver reliable solutions, monitoring, governance, and data quality improvements. The role involves distributed data systems, real-time analytics, knowledge retrieval, and AI-ready infrastructure, with work based five days per week in Singapore.

Lead architecture, development, and operation of Airwallex's data and AI platforms. Drive company-wide data platform strategy, build scalable multi-region data pipelines, promote best practices, mentor engineers, and enable data-driven decision making and AI readiness across the organization.

Lead user research and market insights to evaluate customer perception of Airwallex. Design qualitative and quantitative studies, synthesize feedback, present data-driven recommendations to leadership, and collaborate with product, engineering, and commercial teams to integrate insights and improve customer experience.

Lead design, build, and operate distributed, large-scale (batch/streaming) data platforms and pipelines. Drive technical decisions, performance optimization, data architecture (lakehouse), tooling standards, third-party integration, and mentor junior engineers to enable company-wide data-driven capabilities.