Data Management Executive

Role & responsibilities

• Build internal tools on Google Sheets, AppSheet, Apps Script and Forms turning manual, paper or WhatsApp-based processes into working systems.
• Use AI to build. Write and debug scripts and formulas with Claude Code / ChatGPT / Gemini. AI writes the draft; you test it and own that it works.
• Structure data part masters, price lists, discount matrices, OE cross-reference tables. Clean keys, validation, lookups. Pricing logic: compounded discounts, GST, landed cost, margin.
• Build dashboards management can read in 30 seconds. Auto-refreshing, not manually updated.
• Ship a working v1 in days, show it to users early, fix what breaks during rollout.
• Document and hand over short user guide, train the daily user, then move to the next build.
• Find the next build — sit with users, spot where hours are lost, propose it with rough time saved.

Preferred candidate profile

• Spreadsheets: lookups, pivots, nested formulas, multi-sheet workbooks where data flows correctly. Understands why a formula breaks.
• Real AI usage: uses an AI assistant for actual work, can describe a specific problem solved with it.
• Has built something unasked — a tracker, bot, website, billing sheet, college tool. Anything that works and someone used. This is the real requirement.
• Self-teaching: learns from docs and YouTube without hand-holding; debugs by reading the error.
• Clear English, written and spoken. Asks when the requirement is unclear. Finishes things.