Senior Data Engineer - Financial Crime - HCM
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Senior Data Engineer - Financial Crime - HCM at GoTymeX: Ho Chi Minh City, Vietnam; Hybrid; Vollzeit. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Ho Chi Minh City, Vietnam, Hybrid
- Role classification: Vollzeit
- Source freshness: checked by JobGrid on 2026-06-10.
- Application path: candidates continue to the employer application page with non-personal referral tags.
About TymeX
TymeX is Tyme Group's Technology & Product Development Hub with a global mission to become serial bank builders.
Our Financial Crime platform plays a critical role in protecting customers and the bank from fraud, money laundering, and other financial crimes using advanced data, analytics, AI, and automation.
About the Role
We’re looking for a Senior Data Engineer to join our Financial Crime team. You’ll be part of the group responsible for building and maintaining high-performance data pipelines that drive fraud detection, entity resolution, and compliance analytics across Tyme’s ecosystem. The ideal candidate should relocate to Vietnam.
You’ll work with large, complex datasets in Databricks, integrate data from multiple systems in real time and batch, and help design the data foundation for real-time risk detection and case management.
Key Responsibilities:
- Build and optimize data ingestion pipelines using Python and PySpark to collect and transform data from multiple sources (transactions, KYC, AML, authentication, devices, logs, etc.).
- Proficiency in SQL (PostGres preferred)
- Design and maintain data model that support Financial Crime/Fraud detection, profiling, and entity resolution.
- Implement data quality checks and ensure data reliability across environments.
- Collaborate closely with Data Scientists, Analysts, Compliance, Operations and our Product/Feature teams to operationalize models and rules.
- Utilize jobs, workflows, APIs and streaming to manage large-scale data processing workloads.
- Integrate with external systems (e.g. sanctions, ID&V, biometrics and authentication systems) to enrich risk and identity data.
- Support automation and monitoring of ETL processes to improve operational efficiency.