Build, maintain, and improve reports and dashboards in Google Sheets that Sales, Customer Success, Finance, and Supports teams rely on to understand business health and inform decision making (pipeline health coverage, ARR movements, key SaaS metrics like NRR, LTV, CAC:LTV ratio and so on).
Support mission critical work around budget modelling, forecasting and timely commissions calculations.
Own data clean-up, deduplication, and enrichment across Salesforce: accounts, contacts, opportunities, subscriptions, and many custom objects we use to track engagement and sales
Write and maintain macros (VBA) and Google Apps Script to automate recurring reporting, data validation, and tool creation.
Investigate data quality issues end-to-end: trace where bad data originates (manual entry, integrations, imports), propose process or system fixes, and implement them.
Partnering with Sales, RevOps, Customer Success, Finance, and Delivery leaders in order to translate ambiguous requirements into clear analyses with clear answers.
Document data definitions, ownership, and report logic so the team isn't dependent on whoever built the sheet last.
Support ad-hoc analysis and contribute to larger data and reporting projects

2-4 years of experience in a data analyst, business analyst, or revenue/sales operations analyst role, ideally in SaaS, professional services, or a business that combines both.
Strong Excel and Google Sheets skill, comfortable with lookups, pivot tables, array formulas, and complex formulas.
Solid working knowledge of the Salesforce data model: objects, relationships, record types, reports, and how data flows in and out via imports, integrations, and user input.
Understanding of how subscription, opportunity, and project/engagement data typically hangs together is desirable
Hands-on experience writing macros (VBA) and/or Google Apps Script to automate workflows
you don't need to be a software engineer, but you should be comfortable reading, writing, and debugging scripts, utilising AI where appropriate.
A genuine instinct for data hygiene: you notice when something looks off, and you care enough to dig in.
Clear communicator. You can explain complex findings to non-technical stakeholders.
Fluent spoken and written English.
Self-directed. In a remote setup, you can prioritise your own work and ask for help when you need it.

Equal Opportunity Employer, not discriminating against any employee or applicant for employment

Data Analyst – LTG

Key skills