Senior Data Engineer, Knowledge Platform

Location: Singapore; work from the Singapore office five days a week.

Company

Airwallex is an AI-native financial operating system providing global payments infrastructure and financial products for businesses.

What you will do

• Design and build scalable batch and streaming data pipelines and data models for Knowledge Platform teams and business domains.
• Turn ambiguous data needs into reliable solutions with engineering and cross-functional stakeholders.
• Own projects end to end, including system and pipeline design, performance, monitoring, data quality, and reliability improvements.
• Build knowledge infrastructure spanning Databricks, ClickHouse, Spark, Kafka, real-time analytics, knowledge retrieval and indexing, model infrastructure, agent capabilities, and AI interaction history.
• Develop evaluation, annotation, feedback, governance, permission, and freshness frameworks for reliable AI operations.
• Raise the standard of technical design and execution through strong engineering judgment, problem-solving, and ownership.

Requirements

• Bachelor’s degree or higher in Computer Science, Information Systems, Finance, Mathematics, or a related field.
• At least five years of experience designing and implementing scalable ETL pipelines, including batch and streaming workflows with technologies such as Apache Kafka or Apache Flink.
• Strong proficiency in SQL, database management systems, data warehousing, and data modelling for business intelligence, machine learning, and operational needs.
• Strong understanding of data schemas, including star, snowflake, normalized, and denormalized designs.
• Familiarity with Google Cloud Platform and modern data infrastructure tools, including Databricks and Airflow.
• Knowledge of data governance practices, the six key governance pillars, and regulatory requirements in the financial industry.
• Strong problem-solving, attention to detail, communication, and collaboration skills, including experience working with globally distributed teams.
• Understanding of AI and interest in applying data engineering and AI in practical and creative ways.

Nice to have

• Experience with distributed or multi-datacenter systems, including data migration, duplication, and consistency challenges.
• Experience in financial services, payments, or fintech.
• Experience with Python or R for data analysis and automation.
• Certification in data management or related technologies.

Culture & Benefits

• Work onsite from the Singapore office five days per week.
• Collaborate with globally distributed teams across a company operating from 27 offices.
• Work on data and AI infrastructure supporting global financial operations and regulated payments.