Online Make.com Specialist Jobs (Work From Home)
Verified Make.com specialist jobs with international employers. Remote, paid in USD, from $7/hr. Apply direct on FindTalent, free for talent.
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How much do online Make.com specialist jobs pay?
| Experience level | Hourly (USD) | Monthly (PHP, full-time) | |
|---|---|---|---|
| Entry level (0–1 yr) | $7–11/hr | ₱67,000–105,000 | |
| Experienced (1–3 yrs) | $11–16/hr | ₱105,000–152,000 | |
| Specialist (3+ yrs / niche) | $16–24/hr | ₱152,000–228,000 |
Typical ranges for remote Filipino specialists, reviewed July 2026. Paid in USD, direct to you.
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Skills employers look for in Make.com specialists
- Make.com scenario design and module configuration: Routers, iterators, aggregators, and error handler routes — ask for a complex scenario they built that uses at least a router and an iterator, and walk through the logic with them.
- Data transformation and mapping: Make.com's built-in data transformation tools — parsing arrays, processing JSON, string manipulation, and date formatting — the platform's data tools are more capable than Zapier's Formatter; verify they use them effectively.
- Webhook configuration and custom API connections: Custom webhook modules and HTTP request modules for apps without native Make.com integrations — a Make.com specialist who cannot work with webhooks is limited to the pre-built module library only.
- Error handling and incomplete execution management: Make.com stores failed scenario runs in an incomplete executions queue — ask how they configure error handler routes and how they process incomplete executions for mission-critical workflows.
- Operation cost optimization: Make.com charges per operation (each module run in a scenario) — a specialist who builds inefficiently designed scenarios with unnecessary module executions will generate higher-than-expected monthly costs.
- Integration breadth across business platforms: HubSpot, Airtable, Shopify, Slack, Google Workspace, and Notion are common Make.com integration targets — ask which specific platform integrations they have built and what data flow complexity each involved.
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