Senior Data Engineer

Airwallex2 days ago

Location

SG - Singapore

Type

Full Time

Level

Senior

Role

Senior Data Engineer

Posted

Mar 12, 2026

Full TimeSenior

The role

Summary

Airwallex, a leading global fintech valued at US$8 billion, seeks a Senior Data Engineer to join their Knowledge Platform team in Singapore. The role focuses on building scalable data models, ETL pipelines, and data governance solutions for their unified payments and financial platform serving over 200,000 businesses worldwide.

What you'll do

Data Model Design: Design and implement robust, scalable data models supporting business intelligence, machine learning, and operational needs

Schema Architecture: Select appropriate schema designs (star schema, snowflake, normalized vs denormalized) based on specific use cases and requirements

ETL Pipeline Development: Build and maintain both batch and streaming ETL pipelines with end-to-end data workflow management

Data Quality Management: Maintain data consistency, traceability, and quality across multiple data sources and domains

Cross-functional Collaboration: Work closely with Data Platform Engineers and Product Managers to identify and resolve data issues efficiently

Data Governance Implementation: Participate in and contribute to data governance strategies, policies, and standards across the organization

SSOT Maintenance: Understand and promote Single Source of Truth concepts throughout data layers and pipelines

AI Integration: Explore and implement practical applications where data engineering and AI work together creatively

Business Translation: Collaborate with business teams to translate data needs into clean, structured, and well-documented models

Multi-datacenter Solutions: Handle data challenges across distributed systems including migration, duplication, and consistency issues

What we look for

Technical

ETL Pipeline ExpertiseMinimum 5 years proven experience designing and implementing ETL pipelines with scalable and reliable data pipeline strategies

Streaming Data TechnologiesExperience with real-time data processing technologies such as Apache Kafka or Apache Flink

Database ManagementProficiency in SQL and database management systems including MySQL, PostgreSQL, and Oracle

Cloud Platform KnowledgeFamiliarity with Google Cloud Platform and modern data infrastructure tools

Data Governance UnderstandingKnowledge of data governance practices and regulatory requirements within the financial industry

Modern Data ToolsExperience with Databricks and Apache Airflow for data processing and workflow orchestration

Education

Bachelor's DegreeBachelor's degree or higher in Computer Science, Information Systems, Finance, Mathematics, or related field

Experience

Senior-Level ExperienceMinimum 5 years of proven experience in data engineering with focus on ETL pipeline development

Financial Industry PreferredExperience with financial industries, payment systems, or fintech platforms is highly valued

Data Modeling ExperienceStrong background in designing robust and scalable data models for various business needs

Skills

Required skills

Advanced SQLExpert-level SQL skills for complex data queries, transformations, and database optimization

ETL Pipeline Development5+ years of hands-on experience building scalable batch and streaming data pipelines

Real-time Data ProcessingProficiency with Apache Kafka, Apache Flink, or similar streaming technologies

Database ManagementExperience with MySQL, PostgreSQL, Oracle, and data warehousing solutions

Cloud InfrastructureWorking knowledge of Google Cloud Platform and modern data infrastructure

Problem-solvingExcellent analytical and troubleshooting skills with attention to detail

CommunicationStrong verbal and written communication skills for global team collaboration

Nice to have

Python/R ProgrammingScripting experience for data analysis, automation, and pipeline development

Financial Industry KnowledgeUnderstanding of fintech, payment systems, and financial regulatory requirements

Data GovernanceExperience with data stewardship, metadata management, and compliance frameworks

AI/ML UnderstandingBasic knowledge of artificial intelligence and machine learning applications in data engineering

Multi-datacenter SystemsExperience with distributed systems, data migration, and consistency challenges

Professional CertificationsData management or cloud platform certifications (GCP, Databricks, etc.)

Compensation & benefits

Stock options

Available

Benefits

Competitive Equity Package

Valuable equity participation in a rapidly growing global fintech valued at US$8 billion

Collaborative Work Environment

Open office spaces designed to foster collaboration and creativity among team members

Fully Stocked Kitchen

On-site kitchen facilities with complimentary food and beverages for all employees

Team Building Events

Regular organized team-building activities and company events to strengthen team bonds

Creative Freedom

Autonomy and flexibility to be creative and innovative in problem-solving approaches

Global Impact Opportunity

Work on products and solutions that impact over 200,000 businesses worldwide

Accelerated Learning

Exposure to cutting-edge fintech technologies and rapid professional development opportunities

Interview process

1
Application Review — Initial screening of resume and technical background focusing on data engineering experience
2
Phone/Video Screen — 30-45 minute conversation with hiring manager discussing background and role fit
3
Technical Assessment — SQL and data modeling exercises, potentially including ETL pipeline design questions
4
System Design Interview — Design a scalable data architecture for a fintech use case, focusing on real-time processing
5
Behavioral Interview — Competency-based interview assessing collaboration, problem-solving, and cultural fit
6
Final Round — Meet with senior team members and discuss specific projects and team integration