Data Ops / Data Engineer

About the role

We are looking for an autonomous, logic‑driven Data Ops / Data Engineer to own a massive telecom dataset and bridge data pipelines with our server environments. The role focuses on building robust ETL workflows with Apache Airflow and Python while managing LAMP/CPanel servers.

Key responsibilities

• Design, develop and maintain automated ETL pipelines using Python and Apache Airflow.
• Ingest, aggregate and reconcile large telecom operator logs (100M+ rows monthly) for financial campaign reporting.
• Architect and automate the monthly update of a “Golden Customer Record” integrating multi‑channel engagement data.
• Manage, monitor and optimise the LAMP stack (Linux, Apache, MySQL/MariaDB, PHP) and CPanel environments across lab, cloud and local setups.
• Implement database partitioning, indexing and tuning to support high‑volume imports without impacting production.
• Collaborate with Group IT support to ensure server uptime, resource allocation and infrastructure stability.
• Ensure all pipelines and storage comply with POPIA and data‑governance standards for PII handling.

Required profile

• Experience handling high‑volume datasets and building data pipelines.
• Strong analytical and problem‑solving abilities with attention to detail.
• Self‑driven attitude, comfortable working independently and diving into server logs.
• Computer Science degree, diploma or equivalent practical experience.

Required skills

• Python
• Apache Airflow
• Linux command‑line
• Apache web server
• MySQL / MariaDB
• PHP
• CPanel administration
• Bash (shell scripting)