Senior Data Engineer

Network Finance; Wes-Kaap; On-site; ZAR 900,000 - 1,800,000; Full time

Job summary

Network Finance is seeking a senior data engineer to design, build, and optimize data pipelines for a complex financial data ecosystem. You will ingest data from 40+ payment networks and internal systems, harmonize disparate sources, and ensure data quality, security, and accessibility.

Collaboration with developers, analysts, and business stakeholders is essential for success. You will implement robust ETL/ELT processes using Python and SQL, leverage Airflow for orchestration, and contribute to

Qualifications

• Degree in a quantitative field such as Information Systems, Computer Science, Mathematics, Statistics, or Finance.
• 8+ years relevant experience in data engineering or related roles.
• Proven experience in Python-based data engineering projects.
• Strong proficiency in SQL and Python for data transformation and automation.
• Experience with data orchestration tools (e.g., Airflow).

Responsibilities

• Develop and maintain robust ETL/ELT pipelines using Python and SQL.
• Ingest and transform data from 40+ payment networks and internal systems.
• Join and harmonize data across transactional databases, accounting systems, and CRMs.
• Implement data quality checks, performance tuning, and monitoring for large-scale pipelines.
• Maintain clear documentation and follow best practices for data architecture and deployment.

Skills

Python

SQL

Data pipelines

Education

Degree in a quantitative field

Tools

Airflow

Job description

Key Responsibilities:

• Data Pipeline Development: Build and maintain robust ETL/ELT pipelines using Python, SQL, and cloudnative tools to ingest and transform data from 40+ payment networks and internal systems.
• Data Integration: Join and harmonize data across diverse sources including transactional databases, accounting systems, and CRM platforms.
• Collaboration & Governance: Work closely with developers, analysts, and business stakeholders to ensure data accuracy, security, and accessibility.
• Monitoring & Optimization: Implement data quality checks, performance tuning, and monitoring for pipelines handling tens of millions of rows monthly.
• Documentation & Standards: Maintain clear documentation and follow best practices for data architecture, version control, and deployment.

Job Experience and Skills Required:

• Degree in a quantitative field (e.g. Information Systems, Computer Science, Mathematics, Statistics, or Finance).
• 8+ years relevant experience in data engineering or related roles.
• Proven experience in python-based data engineering projects.
• Strong proficiency in SQL and Python for data transformation and automation.
• Experience with data orchestration tools (e.g., Airflow).