Senior Data Engineer - Financial Crime - Hcm

Tymex; Johannesburg; Hybrid; ZAR 800 000 - 1 100 000; Full time

Job summary

A global technology company is seeking a Senior Data Engineer to enhance their Financial Crime team. You will develop high-performance data pipelines and ensure data integrity for fraud detection and compliance analytics. The ideal candidate has a Bachelor's degree, 5+ years of experience, and strong skills in Python and PySpark. Enjoy a hybrid working model and be part of an international culture. Competitive salary and performance bonuses are offered.

Benefits

Competitive salary

Performance bonuses

Flexible working hours

International culture

Qualifications

• 5+ years of experience in data engineering or related field.
• Hands-on experience with cloud-based data platforms (preferably AWS).
• Proficient in handling structured and unstructured data.

Responsibilities

• Build and optimize data ingestion pipelines using Python and PySpark.
• Design and maintain data models for fraud detection.
• Ensure data reliability and implement data quality checks.

Skills

Python

PySpark

Advanced SQL

Databricks

AWS

DevOps

MLFlow

git-based version control

collaboration

Education

Bachelor's degree

Tools

Snowflake

Kafka

Job 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, 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 VN.

You will 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.).
• Design and maintain data models 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 the 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.

Requirements

• Must‑Have: Bachelor's degree.
• 5+ years of experience.
• Strong skills in Python, PySpark, Scala and Advanced SQL (preferably PostGres). 
• Hands‑on experience with Databricks, Snowflake, Fabric or similar.
• Experience working with structured and unstructured data in a production environment.
• Experience with Agentic AI, MLFlow, ML models, Eval and secure coding practices (testing / QA).
• Comfortable with cloud‑based data platforms (preferably AWS).
• Good communication skills in English – able to collaborate with cross‑functional teams in an international environment.
• Proficiency working with Text, Delta, Parquet, JSON, CSV, and XML data formats.
• Working knowledge of Spark Structured Streaming.
• AWS infrastructure experience, specifically working with S3.
• Solid understanding of git‑based version control, DevOps, and CI/CD.
• Experience with the Atlassian stack is a plus.
• Knowledge of common web API frameworks and web services.
• Strong teamwork, relationship, and client‑management skills, and the ability to influence peers and senior management to accomplish team goals.
• Willingness to embrace modern technology, best practice, and ways of work.

Nice to Have

• Experience in Financial Crime / AML, KYC, or fraud detection systems.
• Familiarity with Entity Resolution frameworks (e.g., Quantexa, Sensing, open‑source Entity Resolution tools).
• Experience with data streaming frameworks (Kafka, Spark Streaming, MQ).

Benefits

Be part of a mission‑driven team tackling real‑world financial crime problems.

Work with modern data tech stack with Agentic AI and advanced ML.

Hybrid working model with flexible hours.

International and collaborative culture — working with colleagues across Vietnam, Singapore, Philippines and South Africa.

Competitive salary, performance bonuses, and learning support.