Graph Data Engineer - Financial Crime Platform at TymeX

Ho Chi Minh City, , Vietnam -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

0.0

Posted On

22 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Graph Data Modeling, Data Engineering, Graph Databases, Python, PySpark, ETL, Data Quality, Data Performance, Graph Visualization, Entity Resolution, Fraud Detection, AML, KYC, Cloud-Based Data Platforms, Data Science, Analytical Skills, Problem-Solving Skills

Industry

Software Development

Description

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, AI, and automation. About the Role We are seeking a Graph Data Engineer to join the Financial Crime Platform team at TymeX. You’ll play a key role in designing, implementing, and optimizing graph-based data models that uncover relationships across customers, entities, devices and transactions — helping our teams detect fraud, identify hidden connections, and streamline case investigations. You will work with graph databases and visualization tools, collaborating closely with our Data, Compliance, and Product teams to power advanced analytics and case management workflows. Key Responsibilities Design and implement graph data models that represent complex relationships between customers, organizations, transactions, devices, behaviour and events. Build graph data pipelines to extract, transform, and load (ETL) data from multiple internal and external sources. Develop efficient queries and Graph Data Science algorithms to support entity resolution, link analysis, and investigative insights. Work with graph visualization tools to build intuitive investigation tools for investigators and analysts. Collaborate with Financial Crime/Fraud analysts to translate investigation use cases into graph-driven solutions. Optimize data performance and ensure data quality across graph structures. Partner with software engineers and data scientists to integrate graph data into wider Financial Crime/Fraud workflows and detection logic. Must-Have: 3+ years of experience in Data Engineering, Graph Data Modeling, or related fields. Hands-on experience with graph databases (e.g., Neo4j, TigerGraph, JanusGraph, Neptune or similar). Proficiency in Python or PySpark for data manipulation and integration on Databricks. Solid understanding of data modeling, ETL, and query languages (Cypher preferred). Strong analytical mindset and problem-solving skills. Good English communication skills (written and verbal). Ability to work effectively in cross-functional, international teams. Nice to Have: Experience with graph visualization tools (Bloom, Linkurious etc) Knowledge of Entity Resolution, Fraud Detection, or AML / KYC systems. Experience integrating graph databases with case management or Financial Crime/Fraud workflows. Familiarity with cloud-based data platforms (AWS). Join a mission-driven product tackling real-world financial crime challenges through data and technology. Work with modern graph technologies and cutting-edge data platforms. Collaborate with global teams across Vietnam, Philippines, Singapore, and South Africa. Hybrid working model, flexible hours, and a diverse, inclusive environment. Competitive salary and professional growth opportunities.

Responsibilities

Design and implement graph data models to represent complex relationships and build graph data pipelines for ETL processes. Collaborate with cross-functional teams to optimize data performance and integrate graph data into financial crime workflows.