Director, Data and Knowledge Platform Engineering

Airwallex

Director, Data and Knowledge Platform Engineering at Airwallex owning architecture, delivery, and adoption of a governed Data → Knowledge → Skills stack for analytics and decisioning.

Posted 7/13/2026full-timeSan Francisco • California • 🇺🇸 United StatesLead💰 $300,000 - $330,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in architecting and scaling modern data platforms, with a strong focus on data governance, semantic layers, and operational excellence. Proven ability to lead engineering teams and drive the adoption of data solutions that enhance analytics and decision-making capabilities.

Highest-signal resume keywords

Data Platform ArchitectureData Modeling ExpertiseGoverned Semantic Layer DesignDatabricks Lakehouse FamiliarityData Governance and Privacy

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ModelingData Quality PracticesMetadata SystemsKnowledge GraphsAPIs DevelopmentOrchestration FrameworksAnalytical WorkflowsData Localization StrategiesRegulatory Controls

Soft Skills

LeadershipCollaborationCommunication

Tools & Technologies

DatabricksData LakehouseAI AgentsAnalytics Platforms

Industry Keywords

Data GovernanceMulti-Jurisdictional CompliancePlatform-as-Product MindsetSLAs/SLOs

About the role

Key responsibilities & impact

Own the architecture, delivery, and adoption of a governed, reusable Data → Knowledge → Skills stack that powers analytics, AI agents, and real-time decisioning across the company.
Design and scale the semantic and operational layers on top of our Data Lakehouse (Databricks), enforce strong governance and lineage, and productize capabilities.
Create a shared foundation that enables both human analysts and AI agents to reason consistently and act confidently.
Partner closely with Data Science, AI engineering, Product, and Risk teams to ensure the platform supports rapid experimentation, intelligent automation, and high-quality decision-making.

Requirements

What you’ll need

15+ years in data or platform engineering, with 5+ years leading engineering teams in complex, multi-region environments.
Proven experience architecting and scaling modern data platforms that extend beyond storage to include semantic layers, metadata systems, or knowledge graphs.
Strong hands-on expertise in data modeling (transactional, event-driven, dimensional, feature tables) with robust data quality, lineage, and observability practices.
Experience designing and operationalizing a governed semantic layer with standardized, auditable business metric definitions.
Track record of building reusable, programmatic capabilities on top of data platforms (APIs, orchestration frameworks, analytical workflows, agent-callable tools).
Deep familiarity with modern lakehouse architectures, particularly within a Databricks environment.
Experience implementing regional data localization and residency strategies while maintaining a unified global data model.
Strong understanding of data governance, privacy, and regulatory controls in multi-jurisdictional contexts.
Platform-as-product mindset, with experience driving adoption, improving developer experience, and operating with clear SLAs/SLOs and measurable impact.

Benefits

Comp & perks

Medical, dental, and vision insurance
401(k) plan
Short-term and long-term disability
Basic life insurance
Well-being benefits
20 paid days of vacation
12 paid days of company holidays in a calendar year