Data Engineer II

12 hours ago

Singapore Airwallex Full time

Overview Data Engineer II (Modeling, ETL) at Airwallex Airwallex is the only unified payments and financial platform for global businesses. Powered by proprietary infrastructure and software, we empower over 150,000 businesses worldwide with integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale. Proudly founded in Melbourne, Airwallex has a team of over 1,800 across 26 offices and is backed by leading investors. If you’re ready to do the most ambitious work of your career, join us. Attributes we value include builder mindset, ownership, fast execution with good judgment, curiosity, and collaboration. You’ll tackle complex, high-visibility problems with exceptional teammates and grow your career as we build the future of global banking. What You’ll Do Part 1. Data Modeling Design and implement robust and scalable data models that support business intelligence, machine learning, and operational needs. Understand data schemas and select appropriate designs (e.g., star schema, snowflake, normalized vs denormalized) based on use cases. Collaborate with business teams to translate data needs into clean, structured, and well-documented models. Promote the concept of SSOT (Single Source of Truth) across data layers and pipelines. Maintain data consistency, traceability, and quality across multiple data sources and domains. Part 2. ETL and Data Pipeline Management Experience building and maintaining both batch and streaming ETL pipelines from data ingestion to transformation and delivery. Work closely with Data Platform Engineers (DPEs) and Product Managers (PMs) to identify root causes of data issues and provide scalable solutions. Bonus if you’ve worked with data across distributed or multi-datacenter systems, including data migration, duplication, and consistency challenges. Part 3. Data Governance Participate in data governance strategies, policies, and standards. Be familiar with the six pillars of traditional data governance: data quality, data stewardship, metadata management, master data management, data privacy/security, and data lifecycle. Part 4. Data + AI Have a basic understanding of AI and think about how data engineering and AI can work together in practical and creative ways. These four areas are the main focuses of the DE team. It’s ideal to be strong in at least one, especially data modeling or data ETL. Additional experience in other areas is a plus. Who You Are Minimum qualifications are required; preferred qualifications are beneficial but not mandatory. Minimum Qualifications Bachelor’s degree in Computer Science, Information Systems, Finance, Math or a related field (master’s degree a plus). At least 2 years of data engineering experience. Proficiency in SQL, database management systems (e.g., MySQL, PostgreSQL, Oracle), and data warehousing solutions. Familiarity with Google Cloud Platform (GCP), specifically BigQuery and Airflow. Excellent problem-solving, attention to detail, and commitment to high-quality work. Strong communication and collaboration skills for a fast-paced, team-oriented environment. Outstanding verbal communication for effective interaction with overseas teams. Preferred Qualifications Experience with financial industries,

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