Enterprise data API platform

Challenge

A data company was preparing an API platform for external developers and enterprise clients. The product included API documentation, authentication, a developer dashboard, usage tracking, and admin tooling, so the team needed confidence in both API behavior and the surrounding platform experience before production launch.

My role

I supported project management and QA. I used Postman for endpoint testing, performed regression testing, tracked issues in Google Docs, and documented bugs for the delivery team.

Approach

The QA approach combined API-level validation with platform-level review. I tested request behavior and endpoint responses while also watching for display bugs and inconsistencies that could create friction for technical and enterprise users.

Work performed

• Tested API endpoints against expected request and response behavior.
• Used Postman to surface request-structure issues.
• Performed regression testing before production release.
• Identified display bugs across the developer and admin platform experience.
• Tracked issues in Google Docs and helped communicate QA status.

Outputs

• Endpoint testing notes.
• Regression testing coverage.
• Postman-surfaced request-structure findings.
• Display bug reports and launch-readiness feedback.

Outcome

The API platform reached production launch with QA support across endpoint behavior, request structure, regression coverage, and user-facing platform issues.

Constraints

• Client and product names anonymized.
• Data categories generalized.
• No invented usage or customer metrics.