Data Analyst (Water Intelligence)

Must Have: - Relevant degree. BSc / BEng / BCom in data science, statistics, informatics, engineering, or a quantitative field - completed. - 1–5 years working with real data (analytics, reporting, engineering data, billing/consumption data, or similar). Strong internship or project evidence counts at the junior end. - Excel to advanced level (pivots, lookups, Power Query a plus) AND at least one of SQL or Python (pandas) - AI proficiency - Numerical scepticism - Clear writing

Strongly preferred: - Utilities, metering, telemetry, or building services data exposure; time-series analysis; municipal tariff literacy. - Dashboarding (Power BI or similar); basic scripting for automation; version-control habits. - Evidence of self-built tools: a tracker, a pipeline, a validation script others actually used.

Key responsibilities: Consumption & billing analytics - Baseline demand from municipal bills and meter data; annualise partial windows correctly; flag data gaps as findings, not footnotes. - Benchmark sites against portfolio and sector norms; identify and rank savings opportunities with rand values attached. - Analyse tenant billing and recovery data to quantify unrecovered water on multi-tenant sites.

Telemetry & monitoring - Work with logger and telemetry data: channel validation, night-flow analysis, burst and leak signatures, alarm triage. - Apply and refine data-quality rules (implausible readings, stuck meters, clock drift) so alerts are trusted.

Reporting & verification - Produce the tables, charts and appendices for audit reports and portfolio reviews in house style. - Track actual performance of delivered projects against design intent; quantify realised savings honestly.

Data stewardship - Keep the property, meter and project registries accurate and current; run exception queues to zero. - Document every recurring analysis so it is repeatable by someone else — no black boxes, no key-person spreadsheets.