Senior Data Platform Engineer (Knowledge Platform & AI Enablement)

Airwallex1 weeks ago

Location

SG - Singapore

Type

Full Time

Level

Senior

Role

Data Engineer

Posted

Mar 6, 2026

Full TimeSenior

The role

Summary

Senior Data Platform Engineer role at Airwallex Singapore, focusing on building next-generation data platform with AI enablement capabilities. The role involves designing and implementing large-scale distributed data processing systems, working with Lake House architectures, and optimizing data storage and processing to enable data-driven decision making across the organization.

What you'll do

Technical Decision Making: Engage in technical decision-making, custom development, integration, and performance optimization at the foundational level

System Development: Develop and automate large-scale, high-performance distributed data processing systems for batch and streaming workloads

Infrastructure Design: Design and build scalable data infrastructure and pipelines using modern data engineering practices

Data Processing Optimization: Optimize data storage, processing, applications, and interfaces to reduce latency and improve efficiency

Architecture Implementation: Implement and evaluate new data architectures including Lake House patterns for improved data accessibility

Tool Standardization: Define shared data engineering tool standards to enhance productivity across the engineering organization

Team Leadership: Provide technical guidance and mentorship to junior engineers and Data Platform Engineer II roles

Cross-functional Collaboration: Work with product teams, data scientists, and business stakeholders to enable data-driven decision making

Performance Monitoring: Monitor and optimize system performance, ensuring high availability and reliability of data platforms

Third-party Integration: Develop integration solutions for third-party data sources and external systems

What we look for

Technical

Data Engineering Experience5+ years of hands-on experience in data engineering roles

Programming LanguagesProficiency in Kotlin, Java, Scala, Python, and SQL

Distributed SystemsExperience designing, building, and operating distributed systems

Big Data TechnologiesWorking knowledge of Kafka, Spark, Flink, Hadoop, and DBT

Cloud Data PlatformsExperience with BigQuery, Snowflake, and cloud data lakes

Real-time ProcessingStrong knowledge of real-time and batch processing systems

Petabyte Scale DataExperience working with data at petabyte scale

Data ArchitectureAbility to establish overarching data architecture and design patterns

Education

Bachelor's DegreeBachelor's or Master's degree in Computer Science, Computer Engineering, Computer Information Systems, or equivalent experience

Experience

Senior-level EngineeringExperience leading system design and driving medium to large-scale projects

Mentorship ExperienceExperience providing technical guidance and mentorship to junior engineers

Financial TechnologyExperience in fintech or financial services industry preferred

Cross-border PaymentsUnderstanding of global payments and financial platforms is advantageous

Skills

Required skills

Java/Kotlin/ScalaStrong proficiency in JVM languages for enterprise data platform development

PythonAdvanced Python skills for data processing and automation

SQLExpert-level SQL for complex data queries and transformations

Apache SparkProduction experience with Spark for large-scale data processing

Apache KafkaReal-time streaming data processing with Kafka

Distributed SystemsDeep understanding of distributed system design principles

Data ArchitectureAbility to design and implement scalable data architectures

System DesignSenior-level system design capabilities for complex data platforms

Nice to have

Apache FlinkStream processing framework for advanced real-time analytics

DBTModern data transformation tool for analytics engineering

Spring BootMicroservices development for data platform services

BigQueryGoogle Cloud data warehouse experience

SnowflakeCloud data platform expertise

Hadoop EcosystemTraditional big data processing frameworks

Lake House ArchitectureModern hybrid data architecture patterns

Financial TechnologyDomain knowledge in fintech and payment systems

Compensation & benefits

Benefits

Global Impact

Work on solutions that serve over 200,000 businesses worldwide including major brands

Career Growth

Accelerated learning opportunities in a fast-growing fintech valued at $8 billion

Innovation Focus

Work with cutting-edge technology and AI to solve complex global payment challenges

Diverse Environment

Join a team of 2,000+ innovative professionals across 26 global offices

Equity Opportunity

Be part of a company backed by world-leading investors including Visa, Mastercard, and Sequoia

Equal Opportunity

Inclusive workplace that values diversity and provides accommodation for special needs

Interview process

1
Application Review — Initial screening of resume and technical background
2
Recruiter Phone Screen — 30-minute conversation about role fit and career goals
3
Technical Assessment — Coding challenge or take-home assignment focusing on data engineering problems
4
Technical Interview Round 1 — System design interview focusing on data architecture and distributed systems
5
Technical Interview Round 2 — Deep-dive technical discussion on big data technologies and past projects
6
Behavioral Interview — Leadership and collaboration assessment with focus on mentorship capabilities
7
Final Interview — Meeting with hiring manager and senior team members
8
Reference Check — Verification of past performance and technical capabilities