Manager, Data Engineering

Airwallex is the AI-native financial operating system for a real-time intelligent economy. More than 676000 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. Were 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.

Were co-headquartered in San Francisco and Singapore with more than 2300 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.

The Data & AI org is at the heart of our companys data and AI strategy. We are building the foundational infrastructure that empowers the entire company to leverage data AI and ML into business impact. We accomplish this by creating platforms that handle the entire data and AI/ML lifecycle simplifying the interface while providing proper safety and governance. This includes managing our data infrastructure (Databricks Spark Kafka etc.) the technology to serve that data to our users (RAG MCP etc.) and the platform to host and govern these AI/ML models.

In 2026 our teams overarching mission is to evolve our full data ecosystemencompassing both platform and modelsinto a fully AI agent-ready infrastructure; we will empower customers to engage directly with the data platform to extract actionable value through capabilities like analytics and natural language querying while also upgrading the platform to deliver robust real-time performance for instant data-driven decision-making.

Were looking for a Data Engineering Manager to lead a team within our Strategic Data Org and help scale the data foundations that power Airwallexs products analytics and operational this role you will lead engineers working on data modeling pipelines and analytics-ready datasets across domains such as regulatory reporting data content foundation customer and business data and growth data. Youll partner closely with engineering leaders product and business stakeholders and adjacent platform teams to turn ambiguous business needs into reliable well-structured data solutions.

This is a hybrid role based in San Francisco.

Team Leadership & People Management

• Hire coach and grow a team of data engineers setting clear expectations and providing regular feedback and career development support.

• Establish team rituals priorities and ways of working that balance delivery speed with engineering rigor.

• Act as a technical mentor reviewing designs and code where needed and helping engineers grow their skills in data modeling pipeline engineering and governance.

• Manage performance workload and hiring plans in line with business needs.

• Drive AI strategy and AI automation for the team.

Data Modeling Strategy

• Set the technical direction for data modeling across the team ensuring the org selects appropriate schema designs (e.g. star schema snowflake normalized vs. denormalized) based on business use cases.

• Champion the concept of Single Source of Truth (SSOT) across data layers and pipelines and hold the team accountable to it.

• Ensure your team collaborates effectively with business stakeholders to translate data needs into clean structured well-documented models.

• Oversee data consistency traceability and quality standards across multiple data sources and domains.

ETL & Data Pipeline Oversight

• Guide the teams approach to building and maintaining batch and streaming ETL pipelines from ingestion through transformation and delivery.

• Ensure strong collaboration between your team Data Platform Engineers (DPEs) and Product Managers (PMs) to drive quick root-cause resolution of data issues and durable scalable fixes.

• Bring judgment to challenges around distributed or multi-datacenter systems including data migration duplication and consistency and help the team navigate them.

Data Governance

• Own and evolve data governance strategy policies and standards for the teams domains.

• Ensure the teams practices reflect the key pillars of data governance (data quality data stewardship metadata management master data management data privacy/security data lifecycle).

• Represent the data engineering team in cross-functional governance conversations and decisions.

Data AI

• Drive thinking on how data engineering and AI can work together in practical high-impact ways and help the team build the foundations that make that possible.

These areas data modeling ETL/pipelines governance and data AI are the core focuses of the DE team. You should have strong credible expertise in at least one (ideally data modeling or ETL) with working knowledge across the others.

Minimum Qualifications:

• Bachelors degree or higher in Computer Science Information Systems Finance Mathematics or a related field.

• 8 years of experience designing and implementing ETL pipelines using tools such as Informatica Talend Apache NiFi or similar data integration platforms including significant hands-on technical depth.

• 2 years of experience directly managing or leading data engineers including hiring coaching and performance management.

• Proficiency in SQL database management systems (e.g. MySQL PostgreSQL Oracle) and data warehousing solutions.

• Familiarity with Google Cloud Platform (GCP) specifically BigQuery and Airflow.

• Demonstrated ability to set technical direction and drive alignment across engineering and business stakeholders.

• Excellent problem-solving skills with a keen attention to detail and a commitment to producing high-quality work.

• Strong communication and collaboration skills with the ability to lead effectively in a fast-paced team-oriented environment and work with globally distributed teams.

Preferred Qualifications:

• Experience with financial industries payment systems or fintech platforms.

• Knowledge of data governance practices and regulatory requirements in the financial industry.

• Experience with scripting languages (e.g. Python R) for data analysis and automation.

• Certification in data management or related technologies.

• Prior experience scaling a data engineering team through periods of significant company growth.

To protect you from recruitment scams please be aware that Airwallex will not ask for bank details sensitive ID numbers (i.e. passport) or any form of payment during the application or interview process. All official communication will come from an @ email address. Please apply only through or our official LinkedIn page.

Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition regardless of any other provision to the contrary.

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 dont 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.

Required Experience:

Manager