Senior Data & Ai Engineer - Financial Crime

Tyme Group; Gauteng; Hybrid; ZAR 300 000 - 400 000; Full time

Job summary

A technology and product development hub in South Africa is seeking a Senior Data & AI Engineer for their Financial Crime team. In this role, you'll build and maintain high-performance data pipelines for fraud detection and compliance analytics. Candidates should have extensive experience with Python, PySpark, and AWS, as well as a Bachelor's degree. Benefits include a hybrid working model, competitive salary, and a mission-driven team tackling real-world financial crime problems.

Benefits

Hybrid working model with flexible hours

Competitive salary and performance bonuses

Learning support

Qualifications

• 5+ years of experience in data engineering, focusing on Financial Crime/AML.
• Strong skills in Python, PySpark, and SQL (preferably PostGres).
• Experience with Databricks and cloud-based data platforms (preferably AWS).

Responsibilities

• Build and optimize data ingestion pipelines using Python and PySpark.
• Design and maintain data models for Fraud detection.
• Collaborate with cross-functional teams to operationalize models.

Skills

Python

PySpark

SQL

Databricks

Cloud platforms (AWS)

DevOps

CI/CD

Data processing

Hands-on experience with ML models

Education

Bachelor's degree

Tools

Databricks

Snowflake

MLFlow

Job description

About TymeX

TymeX is the 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 & AI Engineer to join our Financial Crime team.

You will 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.

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 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 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.

Requirements

• 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.
• 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 in 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 working on Atlassian stack 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.