Manager, FP&A Data

Airwallex
SG - SingaporePosted 1 April 2026

Job Description

Manager, FP&A Data 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 200,000 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 2,000 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 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 https://www.airwallex.com/us/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. What you’ll do As the technical engine within the FP&A team, you will be responsible for overseeing financial data maintenance and building the necessary infrastructure to transform raw financial data into automated, strategic insights through dashboards, context files, and management reports. This role demands deep technical capability and a continuous improvement mindset, focusing on high-stakes data governance and workflow automation. You will move away from traditional manual spreadsheets toward AI-native solutions, leveraging SQL, Python, AI, and Large Language Models (LLMs) to build and own the FP&A data infrastructure roadmap. You will partner directly with our Data & AI Engineering team to maintain automated pipelines connecting our internal systems to our central data warehouse. Your key goal is to eliminate manual data manipulation by designing live, self-updating dashboards and management reports that track business metrics and outcomes and create automated workflows that react to real-time business changes. Responsibilities - Build and maintain automated data pipelines that pull information from our payment systems and ERP into the finance data warehouse. - Use AI-assisted coding and languages like Python and SQL to automate manual data reconciliation and reporting tasks, such as transaction matching, expense categorization, and report generation. - Perform daily and monthly data 'sense checks' and act as the custodian for data integrity in our FP&A systems, including creating and maintaining data logic and troubleshooting data discrepancies. - Architect the finance tables in cloud data warehouses (e.g., Snowflake or BigQuery) to establish a single, reliable source for all company metrics. Serve as the central FP&A focal point for storing and maintaining all datasets, including historical actuals, forecasts, and budgets, within the corporate data foundation. - Design live, self-updating dashboards that track company performance, margins, and burn rates, and create automated reports for analysis such as product-level P&L. - Partner with the engineering team to ensure new product features or payment methods are correctly captured in our financial data models. - D ... (truncated, view full listing at source)
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