Director, Data Platform Engineering (relocate to Singapore)

Airwallex4 days ago

Location

US - San Francisco

Type

Full Time

Salary

USD 300,000 – 330,000

Level

Director

Role

Engineering Manager

Posted

Mar 10, 2026

Full TimeDirector

The role

Summary

Airwallex is seeking a Director of Data Platform Engineering to relocate to Singapore and lead the architecture and delivery of their comprehensive Data → Knowledge → Skills platform. This role involves building governed data infrastructure on Databricks, implementing semantic layers for AI agents and analytics, and managing global data localization strategies across multiple regions while maintaining compliance.

What you'll do

Platform Architecture Leadership: Design and scale the three-layer Data → Knowledge → Skills platform architecture across multiple regions and use cases

Data Platform Management: Own the architecture, delivery, and adoption of governed, reusable data infrastructure built on Databricks Lakehouse

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

Global Data Localization Strategy: Implement regional data residency and compliance strategies while maintaining unified global data models across priority markets

Cross-Functional Collaboration: Partner with Data Science, AI Engineering, Product, and Risk teams to enable rapid experimentation and intelligent automation

Team Leadership and Development: Lead and mentor engineering teams in complex, multi-region environments with focus on platform-as-product mindset

Data Governance Implementation: Establish robust data quality, lineage, and observability practices with strong regulatory compliance controls

API and Tools Development: Build reusable analytical workflows, agent-callable tools, and transformation primitives for automated decision-making

Platform Adoption and SLAs: Drive platform adoption, improve developer experience, and operate with clear SLAs/SLOs and measurable impact metrics

AI Agent Integration: Enable AI agents and machine learning systems to reason consistently and act confidently using platform capabilities

What we look for

Technical

Data Platform ArchitectureProven experience architecting and scaling modern data platforms beyond storage to include semantic layers and knowledge graphs

Databricks ExpertiseDeep familiarity with modern lakehouse architectures, particularly within Databricks environments

Data Modeling MasteryStrong hands-on expertise in transactional, event-driven, dimensional, and feature table modeling

Semantic Layer DesignExperience designing and operationalizing governed semantic layers with standardized business metric definitions

Multi-Region ComplianceExperience implementing regional data localization and residency strategies in multi-jurisdictional contexts

Platform DevelopmentTrack record building reusable, programmatic capabilities including APIs, orchestration frameworks, and analytical workflows

Data GovernanceStrong understanding of data governance, privacy, and regulatory controls with robust quality and lineage practices

Education

Advanced Technical DegreeBachelor's or Master's degree in Computer Science, Data Engineering, or related technical field preferred

Continuous LearningDemonstrated commitment to staying current with modern data platform technologies and architectural patterns

Experience

Senior Leadership Experience15+ years in data or platform engineering with 5+ years leading engineering teams in complex environments

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

Enterprise Scale SystemsProven experience scaling data platforms for large enterprise environments with high availability requirements

Skills

Required skills

Data Platform LeadershipExecutive-level experience architecting and scaling enterprise data platforms with semantic layers

Databricks LakehouseExpert-level proficiency with Databricks ecosystem including Delta Lake, MLflow, and Spark optimization

Multi-Region Data ArchitectureAdvanced skills in designing data residency and localization strategies across global markets

Team ManagementProven leadership abilities managing distributed engineering teams in complex technical environments

Data GovernanceDeep expertise in implementing enterprise-grade data quality, lineage, and compliance frameworks

API and Platform DesignStrong background in building reusable, programmatic data platform capabilities and developer tools

Nice to have

AI/ML Platform IntegrationExperience enabling AI agents and machine learning systems through data platform capabilities

Financial Services DomainBackground in fintech, payments, or financial services data platforms and regulatory requirements

Cloud-Native ArchitectureExpertise with cloud-native data platform patterns and multi-cloud deployment strategies

Real-Time ProcessingExperience with streaming data architectures and real-time decisioning systems

Knowledge Graph TechnologiesFamiliarity with semantic technologies, ontologies, and knowledge representation systems

DevOps and InfrastructureStrong background in infrastructure as code, containerization, and platform automation

Compensation & benefits

Salary

USD 300,000 – 330,000 (annual)

Stock options

Available

Benefits

Relocation Support

Comprehensive relocation package to Singapore including visa sponsorship and moving assistance

Global Technology Exposure

Opportunity to work with cutting-edge fintech infrastructure serving 200,000+ businesses worldwide

Leadership Development

Executive-level role with direct impact on company-wide data strategy and AI initiatives

International Team Collaboration

Work with 2,000+ innovative technologists across 26 global offices

Equity Participation

Opportunity to participate in the growth of a US$8 billion valued unicorn company

Career Growth Potential

Platform leadership role in a rapidly scaling fintech with strong investor backing

Technical Innovation

Lead development of next-generation data platform supporting AI agents and real-time decisioning

Interview process

1
Initial Screening — Phone or video call with talent acquisition to discuss background, relocation requirements, and role alignment
2
Technical Leadership Interview — Deep-dive technical discussion on data platform architecture, scaling challenges, and leadership philosophy
3
System Design Session — Comprehensive system design exercise focusing on multi-region data platform architecture and governance
4
Executive Panel Interview — Leadership assessment with senior engineering and product executives covering strategic vision and team management
5
Cross-Functional Stakeholder Meetings — Interviews with Data Science, AI Engineering, and Product teams to assess collaboration and platform-as-product mindset
6
Final Executive Interview — Discussion with C-level executives on strategic impact, cultural fit, and relocation logistics
7
Reference Checks — Professional references focusing on technical leadership, platform scaling experience, and team management capabilities