Engineering Director, Agentic AI Data Platform

About the role

Airwallex, an AI-native financial operating system used by hundreds of thousands of businesses worldwide, is looking for an Engineering Director for its Agentic AI Data Platform team. Based in San Francisco, the role leads the team responsible for the data backbone of financial systems, setting technical direction for high-volume data ingestion, the Databricks lakehouse, data orchestration, canonical financial models and the infrastructure that keeps the platform reliable, scalable and increasingly real-time. It combines strong technical judgment with people leadership.

Key responsibilities

• Lead and grow a high-performing data platform engineering team, giving technical direction, mentorship and career development.
• Set the technical strategy for high-volume financial data ingestion from payment processors, banks, billing systems and ERP/GL platforms, with guarantees on correctness, replayability and recovery.
• Lead the evolution of the Databricks lakehouse using Spark, Delta Lake, Unity Catalog, dbt, Python and SQL.
• Define standards for data contracts, schema evolution, drift detection, data quality and canonical financial models.
• Evolve the platform from batch toward near-real-time processing with Kafka, CDC, micro-batching, incremental processing and Dagster orchestration.
• Own the architecture of canonical financial models that feed the accounting engine.
• Partner with infrastructure and platform teams on observability, alerting, incident response, recovery and operational readiness.
• Guide infrastructure strategy across GCP, Terraform, Kubernetes/GKE, Helm, GitOps and CI/CD.
• Lead migrations from legacy pipelines to the lakehouse with parity validation, staged rollouts and rollback plans.
• Drive performance and cost optimization across PostgreSQL, Databricks and large-scale workloads.
• Partner with product, accounting, ML and platform leadership to turn business needs into scalable platform capabilities.
• Champion AI-assisted engineering practices while keeping code quality, testing, security and reliability high.

Required profile

• 8+ years in data platform, backend or infrastructure engineering, including significant experience leading engineering teams.
• Proven experience managing and developing senior engineers and technical leads.
• Deep expertise in data platforms, distributed systems, data modeling and production data pipelines.
• Experience building reliable ingestion systems with large-scale backfills, incremental processing, checkpointing, idempotency and failure recovery.
• Experience with streaming and event-driven architectures, data orchestration platforms, and complex technical migrations.
• Strong technical communication and the ability to influence architecture and engineering decisions across teams.

Required skills

• Python and SQL; Spark, Databricks, Delta Lake, dbt and modern lakehouse architectures.
• Kafka, CDC and micro-batching.
• Dagster and data orchestration.
• PostgreSQL performance tuning.
• GCP, Terraform, Kubernetes/GKE, Helm, GitOps and CI/CD.
• Observability, reliability engineering and production operations.