Backend Engineer (JSON Schema Developer) – Remote/USA

Remote | Contract | Full-Time or Part-Time | $40–$42/hour

Job Overview

A customer-facing team is seeking a highly detail-oriented Backend Engineer (JSON Schema Developer) to help convert complex, unstructured documents into clean, structured, and usable data.

This is a remote contract opportunity that can be done on either a full-time or part-time basis, making it especially appealing for experienced backend engineers, data modelers, and schema specialists who enjoy solving messy information problems with precision.

At its core, this role is about one thing:

Turning large, complex PDF documents into scalable, well-designed JSON extraction schemas.

If you enjoy designing systems from scratch, thinking deeply about data structure, and building logic that makes downstream integrations cleaner and more reliable, this role is likely a strong fit.

Compensation

• $40 – $42 per hour
• Contract-based engagement
• Open to:
  • Full-time
  • Part-time

This flexible structure could make the role attractive to both independent contractors and specialists looking for high-value project work.

Job Type & Location

• Job Title: Backend Engineer (JSON Schema Developer)
• Job Type: Contract
• Work Model: Remote
• Schedule: Full-time or Part-time

Because the work is highly independent and documentation-heavy, it appears well-suited for remote professionals who are comfortable owning technical decisions without constant oversight.

What This Role Is About

The company is looking for someone who can take complex raw documents—especially lengthy PDFs ranging from 25 to 150 pages—and transform them into structured, reusable, and future-ready JSON-based data models.

This is not a generic backend API role.

It is a specialist data-architecture-focused backend role where your main value comes from:

• Analyzing unstructured or semi-structured source documents
• Deciding what information should be extracted
• Designing robust JSON schemas from scratch
• Defining:
  • Field types
  • Required vs. optional logic
  • Nesting patterns
  • Repeating structures
  • Validation rules
• Creating schemas that can support reliable downstream automation and integrations

In other words, you’re not just “writing JSON.”

You’re designing the contract between messy source data and structured systems.

Key Responsibilities

As the Backend Engineer (JSON Schema Developer), you’ll be expected to take ownership of schema design and data structuring decisions across complex document workflows.

Core Responsibilities

You will:

• Review and analyze complex PDF documents (approximately 25–150 pages)
• Identify and model important data points from those documents
• Design comprehensive JSON extraction schemas from scratch
• Determine:
  • Which fields should be extracted
  • Appropriate data types
  • Logical structure and hierarchy
  • Deep nesting relationships
  • Repeating arrays and grouped data patterns
• Embed field-level validation logic directly into schemas, including:
  • Sum validation requirements
  • Null testing
  • Type enforcement
  • Logical constraints
• Define and clearly communicate API contracts to support clean integration across systems
• Collaborate with cross-functional stakeholders to:
  • Clarify data requirements
  • Refine schema decisions
  • Align on expected outputs
• Document each field thoroughly, including:
  • Field name / purpose
  • Required vs. optional status
  • Descriptions
  • Expected type
  • Validation rules
• Promote best practices in:
  • Data architecture
  • Scalability
  • Reusability
  • Consistency in schema design

Required Skills & Qualifications

This role is clearly aimed at someone who is more than a generalist backend developer. The ideal candidate is a schema-first thinker with strong information modeling instincts.

Required Technical Skills

You should have proven experience in:

• Data modeling
• Database design
• Schema development
• JSON Schema (ideally hands-on, not just conceptual familiarity)
• Designing deeply nested JSON structures
• Building schemas from a blank page
• Field typing and data validation logic
• Structuring information extracted from unstructured or complex documents

Technical Depth Expected

The employer is specifically looking for someone who can:

• Think architecturally about data
• Translate raw, messy, document-based information into clean models
• Understand the difference between:
  • Required vs. optional fields
  • Arrays vs. nested objects
  • Flat vs. hierarchical design
  • Flexible vs. strict validation
• Embed logical rules directly into the schema layer

This means the role goes beyond formatting—it requires real judgment about how data should behave in production.

Communication & Work Style

You’ll also need:

• Strong written and verbal communication skills
• The ability to explain technical decisions clearly to non-technical or cross-functional stakeholders
• Confidence working independently in a remote, distributed environment

Preferred Qualifications

While not mandatory, the following would strengthen your fit:

• Experience designing API contracts
• Experience collaborating on integration projects
• Background in extracting structured data from:
  • Variable documents
  • Unstructured sources
  • Inconsistent document formats
• Familiarity with broader data architecture principles
• Experience in fast-paced environments where scalable information models matter

These preferred qualifications suggest the company values people who understand not just schema syntax, but also how schemas function inside larger product or data pipelines.

Ideal Candidate Profile

This role is likely best for someone who is:

• A backend engineer with strong schema expertise
• A data modeler who enjoys building order from ambiguity
• Comfortable with document-heavy, logic-heavy work
• Strong at making architecture decisions without needing hand-holding
• Able to think about:
  • Current extraction needs
  • Future scalability
  • Integration compatibility
  • Maintainability over time

A great fit would likely come from backgrounds such as:

• Backend engineering
• Data engineering
• Information architecture
• API design
• Document intelligence / extraction pipelines
• Enterprise data modeling

How to Apply?

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