Description
About the Role
The Staff Data Platform Engineer, Knowledge Platform role is at the heart of Airwallex's data and AI strategy. You will build the foundational infrastructure that empowers the entire company to leverage data, AI, and ML into business impact.
Key Responsibilities
- Set the technical direction for Airwallex's data and AI platforms, shaping reliable systems that turn data and AI into measurable business impact.
- Lead the identification and resolution of company-wide challenges through scalable data platform solutions, working across teams to influence technical roadmaps and decision-making.
- Build and evolve the infrastructure behind Airwallex's data ecosystem, including Databricks, Spark, Kafka, real-time analytics, knowledge retrieval and indexing, model infrastructure, and agent capabilities.
- Raise the bar on engineering craft, platform governance, security, reliability, and operational excellence while staying hands-on with complex technical problems.
- Mentor engineers and technical contributors, helping build a high-performing team and a culture of innovation, ownership, and continuous learning.
Requirements
Essentials
- 8+ years of experience in data platforms, data engineering, distributed systems, or an equivalent combination of professional and academic experience in a quantitative field.
- Experience leading company-wide initiatives across multiple teams or influencing technical roadmap planning.
- A track record of collaborating with diverse teams and stakeholders to deliver tangible business outcomes.
- The ability to balance execution and velocity with rigorous research, statistical understanding, and scalable system design.
- Experience mentoring and investing in the development of engineers, scientists, and peers.
- Technical leadership experience across significant data platform projects, including ETL frameworks, metrics stores, infrastructure management, and data security.
- Experience building, deploying, and maintaining reliable, multi-region data pipelines at scale.
- Familiarity with workflow and orchestration frameworks such as Airflow or dbt.
Preferred
- Hands-on experience designing data processing patterns for a modern lakehouse architecture.
- Experience designing and developing standard framework modules, high-performance services, and client libraries for big data systems.
- Experience with technologies such as GCP, Databricks, BigQuery, Dataproc, Kafka, Kubernetes, Spark, Dataflow, Google Cloud Storage, and Airflow.
- Excellent written and verbal communication skills, with the ability to tailor technical concepts for leadership, users, and company-wide audiences.
- Experience rapidly evaluating technologies and running proofs of concept to inform architecture decisions.
- Experience thriving in a complex, fast-moving environment.
Work Environment
- You will work from our Singapore office five days a week.
Company Culture
- You will thrive here if you're comfortable owning the roadmap yourself, own the outcome and don't wait for permission to fix what's broken, and are comfortable with ambiguity.
- You enjoy working closely with people across multiple countries and time zones as part of one connected, global team, including flexing your hours occasionally to make that connection work.
- You value in-person collaboration and are happy being in the office five days a week.