Senior Data Engineer - Python & SQL Pipelines

Network Finance

Wes-Kaap

On-site

ZAR 900,000 - 1,800,000

Full time

5 days ago
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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

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

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