Director, Data Platform Engineering

Airwallex4 days ago

Location

SG - Singapore

Type

Full Time

Salary

USD 380,000 – 400,000

Level

Director

Role

Data Engineering Manager

Posted

Mar 10, 2026

Full TimeDirector

The role

Summary

Director of Data Platform Engineering at Airwallex to lead the architecture and scaling of a comprehensive Data → Knowledge → Skills platform that powers analytics, AI agents, and real-time decisioning across the global fintech company's operations. The role requires 15+ years of data platform engineering experience with deep expertise in modern lakehouse architectures, semantic layers, and multi-region data governance strategies.

What you'll do

Platform Architecture: Design and architect the complete Data → Knowledge → Skills platform stack including data layer, semantic layer, and operational capabilities

Global Data Strategy: Own regional and global data localization strategy within Databricks environment, ensuring compliance while maintaining unified global data models

Team Leadership: Lead and scale engineering teams across multiple regions in complex, multi-jurisdictional environments

Governance Implementation: Enforce strong data governance, lineage tracking, and quality controls across all platform components

Semantic Layer Development: Build and maintain standardized business metric definitions and entity relationships for consistent data interpretation

Platform Productization: Transform platform capabilities into reusable, accessible products for both human analysts and AI agents

Cross-functional Collaboration: Partner with Data Science, AI engineering, Product, and Risk teams to ensure platform supports rapid experimentation and decision-making

Operational Excellence: Establish and maintain SLAs/SLOs, monitoring, and measurable impact metrics for the data platform

Regulatory Compliance: Implement data privacy and regulatory controls across multi-jurisdictional contexts while preserving platform functionality

What we look for

Technical

Data Platform Engineering15+ years in data or platform engineering with proven experience in complex, enterprise-scale environments

Modern Lakehouse ArchitectureDeep expertise in Databricks environments and lakehouse architectural patterns

Data Modeling ExpertiseAdvanced skills in transactional, event-driven, dimensional, and feature table modeling approaches

Semantic Layer DesignExperience architecting and implementing governed semantic layers with standardized business metrics

Multi-region Data ArchitectureProven experience with regional data localization and residency strategies

Platform-as-Product MindsetExperience driving adoption, improving developer experience, and operating with measurable SLAs/SLOs

Education

Bachelor's DegreeBachelor's degree in Computer Science, Engineering, Mathematics, or related technical field

Advanced Degree PreferredMaster's degree in Data Science, Computer Science, or Engineering preferred but not required

Experience

Leadership Experience5+ years leading engineering teams in complex, multi-region environments

Platform EngineeringExtensive experience building and scaling data platforms beyond storage to include semantic layers and knowledge systems

Data GovernanceStrong background in implementing data governance, privacy controls, and regulatory compliance frameworks

Reusable Capabilities DevelopmentTrack record building APIs, orchestration frameworks, analytical workflows, and agent-callable tools

Skills

Required skills

Databricks ExpertiseDeep hands-on experience with Databricks platform and lakehouse architecture

Data Engineering Leadership15+ years progressive experience in data engineering with 5+ years in leadership roles

Semantic Layer ArchitectureProven ability to design and implement governed semantic layers with business metric standardization

Multi-region Data GovernanceExperience with regional data localization, residency requirements, and regulatory compliance

Platform ScalingTrack record of scaling data platforms to support enterprise-level analytics and AI workloads

Team LeadershipStrong leadership and team management skills in complex, distributed engineering environments

Nice to have

Fintech Domain KnowledgeUnderstanding of financial services, payments, and cross-border transaction systems

AI/ML Platform ExperienceExperience building platforms that support machine learning and AI agent capabilities

Real-time ProcessingKnowledge of streaming data architectures and real-time decisioning systems

Cloud ArchitectureMulti-cloud deployment experience with focus on data residency and compliance

API DesignExperience designing and implementing data platform APIs and programmatic interfaces

ObservabilityExpertise in data platform monitoring, alerting, and performance optimization

Compensation & benefits

Salary

USD 380,000 – 400,000 (annual)

Benefits

Global Career Growth

Opportunity to work across 26 global offices and lead teams in multiple regions

Cutting-edge Technology

Access to latest data platform technologies and AI/ML infrastructure at scale

High-impact Role

Direct influence on company-wide data strategy and AI capabilities for a $8B+ fintech unicorn

Learning Opportunities

Accelerated learning in fintech, payments, and global financial services domain

Innovation Environment

Work with bleeding-edge technology stack and contribute to next-generation financial platform

Diverse Team

Collaborate with over 2,000 innovative team members across diverse backgrounds and expertise

Interview process

1
Initial Screening — Phone or video call with talent acquisition team to discuss background and role fit
2
Technical Leadership Interview — Deep-dive technical discussion on data platform architecture, scaling challenges, and leadership experience
3
System Design Session — Whiteboard session designing multi-region data platform with semantic layers and governance requirements
4
Stakeholder Interviews — Meetings with Data Science, AI Engineering, and Product teams to assess collaboration and vision alignment
5
Executive Interview — Final interview with senior leadership focusing on strategic vision and cultural fit
6
Reference Check — Verification of leadership experience and technical expertise through professional references