Data & AI Specialist (Storage Optimization / ROT Analysis)

Purpose:

The Data & AI Specialist (Storage Optimization / ROT Analysis) is responsible for leveraging data analytics, artificial intelligence, and automation to optimise of the company's enterprise data storage environment through the identification, analysis, and management of Redundant, Obsolete, and Trivial (ROT) data. The role supports the development and implementation of data-driven strategies to improve storage efficiency, reduce infrastructure costs, enhance information governance, and ensure compliance with data retention, security, and regulatory requirements.

Key responsibilities:

• Develop and implement data analytics and AI-driven solutions to identify, classify, and analyse Redundant, Obsolete, and Trivial (ROT) data across company's enterprise storage environment.
• Perform enterprise-wide storage assessments to identify optimisation opportunities, reduce storage consumption, improve system performance, and lower infrastructure and operational costs.
• Design, implement, and maintain automated data classification, tagging, and lifecycle management processes using AI, machine learning, and data governance technologies.
• Analyse structured and unstructured data to identify duplication, stale data, compliance risks, and opportunities for data archiving, retention, or secure disposal.
• Collaborate with ICT Infrastructure, Information Management, Cybersecurity, Legal, Risk, and business stakeholders to develop and implement enterprise data retention, archiving, and storage optimisation strategies.
• Develop dashboards, reports, and performance metrics to monitor storage utilisation, data quality, ROT reduction initiatives, compliance status, and optimisation outcomes.
• Ensure compliance with organisational policies, POPIA, records management requirements, cybersecurity standards, and applicable regulatory and governance frameworks relating to enterprise data management.
• Research, evaluate, and implement emerging AI, machine learning, and data management technologies to improve data discovery, storage optimisation, information governance, and operational efficiency.

Minimum requirements:

• Minimum 5+ years in data engineering, data management or AI/ML
• Degree in Data Science, Computer Science, Engineering or related
• Proven experience in data classification, storage optimization, and analytics across enterprise platforms (e.g. SharePoint, cloud storage)