Data Analyst
Remote, Bolivia. Full-time. A detail-oriented and analytical Data Analyst is needed to join a growing team. In this role, you will collect, analyze, and interpret data to provide actionable…
Turning data into dashboards and reports that a business can read and act on.
Listings updated 2026-08-26. Jobs on goLance stay open for about 30 days.
Showing 8 of 8 open listings, newest first.
Remote, Bolivia. Full-time. A detail-oriented and analytical Data Analyst is needed to join a growing team. In this role, you will collect, analyze, and interpret data to provide actionable…
Remote, Argentina (Buenos Aires). B2B Contract, full-time. Spain time zone (CET/CEST) required. Initial contract duration approximately 9 months, with possibility of extension. Key…
Remote, Argentina. Full-time. As a Business Intelligence Engineer, you will take full ownership of a data and reporting ecosystem that has been built but never had a dedicated owner. The…
Remote, Philippines (Metro Manila / Taguig City). Full-time. Responsibilities Design, develop, and deploy enterprise-grade Power BI dashboards and reports for Finance, Supply Chain, and HR…
Remote, Philippines. Full-time. Schedule: 9:00 AM – 6:00 PM AEST / 7:00 AM – 4:00 PM PHT. We are seeking a detail-oriented and analytical Data Analyst to support operational and delivery…
Remote, Colombia. Full-time, Monday to Friday 9:00 a.m. – 6:00 p.m. CST. We are looking for a highly analytical, results-oriented Power BI Business Analyst to support Microsoft Fabric…
Remote, Peru. Contract, full-time. Start date: August/September 2026. This role is part of a digital transformation project for a leading regional bank, focused on modernizing digital…
Remote, Costa Rica. Full-time. The Role A highly analytical, hands-on Principal Data Analyst with deep Adobe Customer Journey Analytics (CJA) expertise is needed to join a Web Analytics…
The most common briefs are extraction and ETL: scraping, API pulls, and moving data between systems on a schedule. Beyond that, expect dashboard and reporting builds, data cleaning, and a smaller set of machine learning engagements.
Be concrete about sources and destinations — which systems you pull from, which warehouse or BI tool you deliver into. Clients here describe problems in terms of their stack, so mirroring that language matters.
No. Data extraction and ETL is by some margin the largest subcategory; ML briefs exist but are a minority.
Dashboard work generally lands in mainstream BI and spreadsheet tooling. State which you build in.
Usually they supply access rather than clean data — a good part of the engagement is often making it usable.
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