Data Analyst / BI Specialist

An established food and beverage organisation based in Paarl is seeking an analytical professional to champion data transformation and modernise business reporting. Working within the Systems team on a full-time, hybrid schedule (incorporating one day per week on-site with core working hours and schedule flexibility), the appointed specialist will coordinate data initiatives across SQL architectures, ZAP BI environments, and emerging AI technologies. The position provides an avenue to engineer certified datasets, structure prompts and targets for AI agents, establish robust data governance guardrails, and advance technical skills in Python and enterprise analytics.

**Key Responsibilities:

• Develop, maintain, and enhance BI dashboards, data models, analytical reports, and ZAP BI environments.

• Extract, transform, and evaluate data across SQL databases, API connections, and enterprise data repositories.

• Partner with commercial and operational stakeholders to translate complex technical findings into clear, practical business narratives.

• Automate workflows, refine reporting mechanisms, and produce unified, reliable data assets to support cross-functional systems without data duplication.

• Formulate operational queries into actionable parameters for AI agents; review, test, and audit machine-generated SQL and deliverables for data integrity prior to stakeholder distribution.

• Embed data governance protocols, establishing boundaries for self-service analytics whilst administering a cohesive semantic layer for end users.

• Contribute technical expertise to data warehousing and systems integration initiatives across internal core platforms.

Requirements

• Proven functional exposure to Power BI, ZAP BI, and SQL database environments (or comparable analytical suites).

• Sound grasp of data modelling principles, including star schema, snowflake schema, and tabular versus multi-dimensional structures.

• Practical track record managing API feeds, data pipelines, enterprise warehouses, ERP platforms, and ETL operations.

• Demonstrated competence in prompt crafting alongside hands-on experience using AI-assisted analytical tools.

• Demonstrated capability to audit, validate, and verify the accuracy of AI-generated SQL and reporting outputs against compliance standards.

• Foundational working knowledge of Python for data manipulation (including pandas and basic automation scripts), accompanied by an appetite for technical expansion.

• Working understanding of data governance frameworks and data quality assurance methods.