Airwallex is on the 2026 Best Places to Work list!
Airwallex Logo

Airwallex

Manager, Data Engineering

Posted 9 Days Ago
Hybrid
San Francisco, CA
200K-335K Annually
Senior level
Hybrid
San Francisco, CA
200K-335K Annually
Senior level
Lead and grow a data engineering team to build and maintain data models, batch and streaming ETL pipelines, and governance practices. Partner with platform, product, and business stakeholders to ensure reliable, governed, and scalable data for BI, ML, and operations while driving AI strategy and technical direction.
The summary above was generated by AI
About Airwallex

Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 250,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.

Proudly founded in Melbourne, we have a team of over 2,300 of the brightest and most innovative people in tech across 27 offices around the globe. Valued at US$11 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us.

 
Attributes We Value

We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor.

You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next.

 
About the team

The Data & AI org is at the heart of our company's 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 team’s overarching mission is to evolve our full data ecosystem—encompassing both platform and models—into 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.

 
What you'll do

We’re looking for a Data Engineering Manager to lead a team within our Strategic Data Org and help scale the data foundations that power Airwallex’s products, analytics, and operational decision-making. In 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. You’ll 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 team's 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 team's domains.

  • Ensure the team's 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.

Who You Are

Minimum Qualifications:

  • Bachelor's 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.

Applicant Safety Policy: Fraud and Third-Party Recruiters

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 @airwallex.com email address. Please apply only through careers.airwallex.com 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.

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.

Airwallex New York, New York, USA Office

Airwallex New York City, US Office

Big moves in the Big Apple, Airwallex New York has a new home in Union Square!

Similar Jobs at Airwallex

8 Days Ago
Hybrid
200K-288K Annually
Senior level
200K-288K Annually
Senior level
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Lead and define a 1-3 year technical roadmap for a petabyte-scale realtime data platform. Modernize core data infrastructure, enable realtime analytics and AI-driven features, scale and structure engineering teams, hire and mentor managers and senior ICs, and partner with product and engineering teams to deliver governed, performant data and AI capabilities.
Top Skills: SparkClickhouseCubejsDatabricksElasticsearchGrafanaKafkaMcpPrometheusRagSplunk
15 Hours Ago
Hybrid
160K-250K Annually
Senior level
160K-250K Annually
Senior level
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Lead product security and incident response efforts: design and deploy security controls, hunt and investigate threats using endpoint/network/cloud telemetry, build detections and workflows, perform forensics, and partner with engineering to remediate vulnerabilities and improve secure design.
Top Skills: Alibaba CloudAuthentication SystemsCi/CdCloud VpnEdrEndpoint ToolsFirewallsGCPGoogle SuiteJavaKotlinKubernetesNetwork Traffic LogsOktaPipelinesPythonSplunk
Yesterday
Hybrid
80K-110K Annually
Junior
80K-110K Annually
Junior
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Build and maintain payment reconciliation frameworks and safeguarding controls across global payment flows. Produce reporting and analytics on cash positions, funding needs, and variances. Partner with Product, Engineering, and Ops to design data models and automated workflows, drive process standardization, and provide actionable insights to support Treasury, Finance, and senior management.
Top Skills: Ai ApplicationsData StudioLookerPythonRSQLTableau

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account