Senior Manager, Data Platform - T0

Airwallex-; San Francisco (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Airwallex in San Francisco is seeking a Senior Manager of Data Platform Engineering to lead the data backbone of our financial systems. You will set the direction for high-volume data ingestion, the Databricks lakehouse, and data orchestration to ensure real-time, reliable analytics.

You’ll build a high-performing team, establish platform standards, and partner with product, accounting, and infrastructure to deliver scalable, auditable data foundations.

Qualifications

• 8+ years in data platform, backend, or infrastructure engineering with leadership experience.
• Proven ability to grow senior engineers and technical leads.
• Deep expertise in data platforms, distributed systems, data modeling, and production data pipelines.
• Strong Python and SQL skills; hands-on with Spark, Databricks, Delta Lake, and dbt.
• Experience building large-scale ingestion systems with backfills, incremental processing, checkpointing, and recovery.
• Strong understanding of streaming architectures, including Kafka, CDC, and micro-batching.
• Experience with Dagster for data orchestration and lakehouse patterns.
• Operations experience on GCP; familiar with Terraform, Kubernetes/GKE, Helm, CI/CD.

Responsibilities

• Lead and grow a high-performing data platform engineering team.
• Set technical strategy for high-volume data ingestion and lakehouse architecture.
• Oversee evolution of Databricks lakehouse with Spark, Delta Lake, Unity Catalog, dbt, Python, and SQL.
• Define standards for data contracts, schema evolution, and data quality.
• Advance batch-to-real-time processing using Kafka, CDC, and Dagster orchestration.
• Own canonical financial models powering the accounting engine.
• Partner with infra and platform teams for observability and incident response.
• Guide infrastructure strategy across GCP, Terraform, Kubernetes/GKE, Helm, GitOps, CI/CD.
• Lead migrations from legacy pipelines to the lakehouse with parity validation.
• Drive performance and cost optimization across PostgreSQL and large data workloads.
• Collaborate with product, accounting, ML, and platform leadership.
• Set architecture direction via reviews, docs, and long-term roadmaps.
• Champion AI-assisted engineering practices to boost velocity while ensuring quality.

Skills

Leadership of engineering teams

Data platform architecture

Python programming

SQL proficiency

Distributed systems

Observability & SRE

Data modeling

GCP & Terraform

Tools

Databricks

Spark

Delta Lake

dbt

Kafka

Dagster

Kubernetes

GKE

Terraform

PostgreSQL

Python

Job description

About Airwallex

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 676,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.

We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.

We're co-headquartered in San Francisco and Singapore, with more than 2,300 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.

About the Team

This team designs intelligent, autonomous systems that eliminate financial operations for companies globally. We automate everything from bookkeeping and reconciliation to tax, payroll, forecasting, and document understanding: turning hours of work into seconds. The team blends deep research pedigree with proven industry experience. We operate with high standards, are tool-agnostic, and expect engineers to own problems end-to-end. We collaborate closely, push boundaries responsibly, and ship exceptional work quickly. You’ll solve unprecedented technical challenges using unique, end-to-end financial datasets no one else in the industry has.

About the Role

As a Senior Manager of Data Platform Engineering, you’ll lead the team responsible for the data backbone of our financial systems. You’ll set the technical direction for high-volume financial data ingestion, our Databricks lakehouse, data orchestration, canonical financial models, and the infrastructure that makes our data platform reliable, scalable, and increasingly real-time.

You’ll combine strong technical judgment with people leadership—building a high-performing engineering organization, establishing platform standards, driving major migrations, and partnering closely with product, accounting, and platform teams. You’ll help shape a data platform where correctness, auditability, performance, and operational excellence are foundational.

This role is based in San Francisco.

What You'll Do

• Lead and grow a high-performing data platform engineering team, providing technical direction, mentorship, career development, and clear ownership.

• Set the technical strategy for high-volume financial data ingestion across payment processors, banks, billing systems, and ERP/GL platforms, with strong guarantees around correctness, replayability, and recovery.

• Lead the evolution of our Databricks lakehouse using Spark, Delta Lake, Unity Catalog, dbt, Python, and SQL, optimizing for scale, performance, reliability, and cost.

• 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 using Kafka, CDC, micro-batching, incremental processing, and Dagster orchestration.

• Own the architecture of canonical financial models that transform complex source data into consistent financial objects and relationships powering our accounting engine.

• Partner with infrastructure and platform teams to build reliable production foundations across 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 rigorous parity validation, staged rollouts, and clear rollback strategies.

• Drive performance and cost optimization across PostgreSQL, Databricks, and large-scale data workloads.

• Partner with product, accounting, ML, and platform leadership to translate business needs into scalable data platform capabilities.

• Set technical direction through architecture reviews, design documents, engineering standards, and long-term platform roadmaps.

• Champion AI-assisted engineering practices that improve team velocity while maintaining high standards for code quality, testing, security, and reliability.

What You’ll Need to Have

• 8+ years of experience in data platform, backend, or infrastructure engineering, including significant experience leading engineering teams.

• Proven experience managing and developing senior engineers and technical leads and building strong, autonomous teams.

• Deep expertise in data platforms, distributed systems, data modeling, and production data pipelines.

• Strong experience with Python and SQL, plus hands-on experience with Spark, Databricks, Delta Lake, dbt, and modern lakehouse architectures.

• Experience building reliable ingestion systems with large-scale backfills, incremental processing, checkpointing, rate-limit handling, idempotency, and failure recovery.

• Strong understanding of streaming and event-driven architectures, including Kafka, CDC, and micro-batching.

• Experience with data orchestration platforms such as Dagster and designing for freshness, partitioning, and incremental computation.

• Experience optimizing PostgreSQL and analytical workloads for performance and cost.

• Experience operating production infrastructure on GCP, with familiarity with Terraform, Kubernetes/GKE, Helm, GitOps, and CI/CD.

• Strong understanding of observability, reliability engineering, and production operations.

• Excellent technical communication skills, with the ability to influence architecture and engineering decisions across teams.

• Experience leading complex technical migrations and balancing long-term platform strategy with near-term business priorities.

• Passion for building teams and infrastructure that power reliable, scalable, mission-critical financial systems.

Equal opportunity

Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.