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Design a Therapy Matching Marketplace

Last updated: Apr 6, 2026

Quick Overview

This question evaluates backend system design competency including API design, data modeling, booking consistency, real-time availability handling, search and ranking strategies, scalability trade-offs, and privacy/compliance considerations for sensitive health data.

  • medium
  • Mavenclinic
  • System Design
  • Backend Engineer

Design a Therapy Matching Marketplace

Company: Mavenclinic

Role: Backend Engineer

Category: System Design

Difficulty: medium

Interview Round: Onsite

Design the backend for a marketplace that matches patients with therapists. The platform should support: - Patients searching for therapists by specialty, insurance, location, language, modality, price, and availability. - Therapist profile pages with credentials, specialties, ratings, session types, and accepted insurance. - Real-time or near-real-time appointment slot availability. - Booking, cancellation, waitlists, and reminders. - Ranking the most relevant therapists for a patient. - Preventing double booking and handling stale availability. - Region and licensure constraints for therapists. Discuss the API design, core services, data model, search and ranking strategy, booking consistency model, privacy and compliance considerations for sensitive health data, scaling approach, and key trade-offs.

Quick Answer: This question evaluates backend system design competency including API design, data modeling, booking consistency, real-time availability handling, search and ranking strategies, scalability trade-offs, and privacy/compliance considerations for sensitive health data.

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  • Design an appointment scheduling system - Mavenclinic (medium)
Mavenclinic logo
Mavenclinic
Jan 13, 2026, 12:00 AM
Backend Engineer
Onsite
System Design
1
0

Design the backend for a marketplace that matches patients with therapists.

The platform should support:

  • Patients searching for therapists by specialty, insurance, location, language, modality, price, and availability.
  • Therapist profile pages with credentials, specialties, ratings, session types, and accepted insurance.
  • Real-time or near-real-time appointment slot availability.
  • Booking, cancellation, waitlists, and reminders.
  • Ranking the most relevant therapists for a patient.
  • Preventing double booking and handling stale availability.
  • Region and licensure constraints for therapists.

Discuss the API design, core services, data model, search and ranking strategy, booking consistency model, privacy and compliance considerations for sensitive health data, scaling approach, and key trade-offs.

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