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Airwallex is a unified payments and financial platform serving over 250,000 global businesses. The Data & AI organization is building foundational infrastructure to empower the company to leverage data, AI, and ML for business impact. You will lead a data engineering team within the Strategic Data Org, responsible for scaling data foundations that power Airwallex's products, analytics, and operational decision-making.
In this hybrid San Francisco role, you will manage engineers working on data modeling, pipelines, and analytics-ready datasets across domains including regulatory reporting, data content foundation, customer and business data, and growth data. You'll partner with engineering leaders, product teams, and platform teams to translate ambiguous business needs into reliable, well-structured data solutions.
Key responsibilities include hiring and coaching a team of data engineers with clear expectations, feedback, and career development support. You'll establish team rituals and ways of working that balance delivery speed with engineering rigor, act as a technical mentor reviewing designs and code, and drive AI strategy and automation for the team.
You will set technical direction for data modeling, championing Single Source of Truth across data layers and ensuring clean, structured, well-documented models. You'll guide the team's approach to building batch and streaming ETL pipelines, from ingestion through transformation and delivery, ensuring strong collaboration with Data Platform Engineers and Product Managers for quick issue resolution.
Data governance is a core focus: you'll own and evolve governance strategy, policies, and standards for the team's domains, ensuring practices reflect data quality, stewardship, metadata management, master data management, privacy/security, and lifecycle management. You'll represent the data engineering team in cross-functional governance conversations.
You should have strong, credible expertise in at least one core area—ideally data modeling or ETL—and drive thinking on how data engineering and AI can work together in practical, high-impact ways. The broader team mission is to evolve the full data ecosystem into AI agent-ready infrastructure, empowering customers to engage directly with the data platform for analytics and natural language querying.
