Job description

ABOUT AIRWALLEX Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 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 2,700 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 airwallex.com to see it in full. HOW YOU'LL MAKE IMPACT Our Strategic Data team builds the data foundations that support business intelligence, machine learning, and operational decision-making. You'll help create reliable, scalable data models and pipelines while improving how teams use data across the business. - Design and implement robust, scalable data models that support business intelligence, machine learning, and operational needs. - Select appropriate schema designs—including star schema, snowflake, normalized, and denormalized models—based on the use case. - Partner with business teams to translate data needs into clean, structured, and well-documented models, while promoting a single source of truth across data layers and pipelines. - Build and maintain batch and streaming ETL pipelines across the full data workflow, from ingestion and transformation through delivery. - Maintain data consistency, traceability, and quality across multiple data sources and domains, including distributed or multi-datacenter environments where relevant. - Contribute to data governance strategies, policies, and standards across areas such as data quality, stewardship, metadata, master data, privacy, security, and lifecycle management. - Work with Data Platform Engineers and Product Managers to identify root causes of data issues and deliver efficient, scalable solutions. - Explore practical ways for data engineering and AI to work together across our products and operations. This role is based in San Francisco or Seattle, and you'll be expected to work from the office three days a week. WHAT WE'RE LOOKING FOR ESSENTIALS - Bachelor's degree or higher in Computer Science, Information Systems, Finance, Mathematics, or a related field. - Five or more years of experience designing and implementing ETL pipelines using tools such as Informatica, Talend, Apache NiFi, or similar data integration platforms. - Strong experience with data modeling, data schemas, ETL, and end-to-end data workflows. - Proficiency in SQL, database management systems such as MySQL, PostgreSQL, or Oracle, and data warehousing solutions. - Familiarity with Google Cloud Platform, particularly BigQuery and Airflow. - Excellent problem-solving skills, attention to detail, and commitment to producing high-quality work. - Strong communication and collaboration skills, including the ability to work effectively with globally distributed teams. - Strength in at least one core area of data engineering, particularly data modeling or ETL, with the ability to contribute across the broader data engineering discipline. PREFERRED - Experience in financial services, payments, or fintech. - Knowledge of data governance practices and regulatory requirements in the financial industry. - Experience with scripting languages such as Python or R for data analysis and automation. - Experience working with distributed or multi-datacenter data systems, including data migration, duplication, and consistency challenges. - Certification in data management or related technologies. YOU'LL THRIVE HERE IF - You're comfortable owning the roadmap yourself. - You own the outcome and you don't wait for permission to fix what's broken. - You're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it. - You connect dots across functions and hold the big picture without losing grip on the details. - You simplify complexity rather than hiding behind it. At Airwallex, you can make an impact in a rapidly growing, global fintech. We want you to share in our success, which is why you’ll be offered a competitive salary plus valuable equity within Airwallex. We also like to ensure we create the best environment for our people by providing collaborative open office space with a fully stocked kitchen. We organise regular team-building events and we give our people the freedom to be creative. 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 airwallex.com email address. Please apply only through careers.airwallex.com 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.

Requirements

Must-haves

Design and implement robust, scalable data models that support business intelligence, machine learning, and operational needs.
Select appropriate schema designs—including star schema, snowflake, normalized, and denormalized models—based on the use case.
Partner with business teams to translate data needs into clean, structured, and well-documented models, while promoting a single source of truth across data layers and pipelines.
Build and maintain batch and streaming ETL pipelines across the full data workflow, from ingestion and transformation through delivery.
Maintain data consistency, traceability, and quality across multiple data sources and domains, including distributed or multi-datacenter environments where relevant.
Contribute to data governance strategies, policies, and standards across areas such as data quality, stewardship, metadata, master data, privacy, security, and lifecycle management.
Work with Data Platform Engineers and Product Managers to identify root causes of data issues and deliver efficient, scalable solutions.
Explore practical ways for data engineering and AI to work together across our products and operations.
Bachelor's degree or higher in Computer Science, Information Systems, Finance, Mathematics, or a related field.
Five or more years of experience designing and implementing ETL pipelines using tools such as Informatica, Talend, Apache NiFi, or similar data integration platforms.
Strong experience with data modeling, data schemas, ETL, and end-to-end data workflows.
Proficiency in SQL, database management systems such as MySQL, PostgreSQL, or Oracle, and data warehousing solutions.
Familiarity with Google Cloud Platform, particularly BigQuery and Airflow.
Excellent problem-solving skills, attention to detail, and commitment to producing high-quality work.
Strong communication and collaboration skills, including the ability to work effectively with globally distributed teams.
Strength in at least one core area of data engineering, particularly data modeling or ETL, with the ability to contribute across the broader data engineering discipline.
You're comfortable owning the roadmap yourself.
You own the outcome and you don't wait for permission to fix what's broken.
You're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it.

Nice-to-haves

Experience in financial services, payments, or fintech.
Knowledge of data governance practices and regulatory requirements in the financial industry.
Experience with scripting languages such as Python or R for data analysis and automation.
Experience working with distributed or multi-datacenter data systems, including data migration, duplication, and consistency challenges.
Certification in data management or related technologies.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningsqlpython

Platform: ashby
Effort: quick

Benefits

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