Data Analyst (Water Intelligence)

- 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.