JSON-LD Experts in Germany
in minutes from over 15,000 CVs with the power of AIHire experts who structure product data, schema.org markup, and linked data for search, apps, and APIs. They can add clean JSON-LD to websites, validate structured data, and keep implementation aligned across teams, with fast, precise matching to vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used JSON-LD
Fred Hauschel
Last position:
Software Architect and Developer at Personal project
A recurring problem in my own AI-supported projects: requirements analysis, use cases, and architecture decisions can be created quickly with AI support, but they remain hard to trace and scattered across Markdown files – knowledge is lost as soon as it is no longer in the context window. arknet turns requirements engineering and architecture knowledge into structured, verifiable data instead of plain text: requirements, use cases, and architecture decisions as a continuously linked knowledge graph, traceable from the requirement to the architecture decision – queryable for both people and AI agents alike. Technically based on RDF/OWL and its own MCP server.
Result: MCP daemon running, Docker image automatically published on GHCR, nine hexagonal modules, eleven ADRs (including an open-core licensing model). Requirements engineering and ubiquitous language hexagon active. Publicly available since 07/2026 as a Community Edition under Apache-2.0 (github.com/kogn-io/arknet), together with the Claude Code plugin and the GHCR image; open-core model.
Label: Java, Maven, RDF, RDF4J, OWL, SPARQL, Model Context Protocol, Spring AI, Docker, GitHub, Git, Claude Code, Obsidian, DDD, Hexagonal Architecture, ArchUnit, JUnit, AssertJ
Prasad Tilloo
Last position:
Solution Architect / Senior Manager – DTC E-Commerce Platform at BRITA
- Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
- Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
- Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
- Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
- Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
- Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
- Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka
Robin Walter Scherler
Last position:
Developer at agentic-engineer.online
agentic-engineer.online is my publicly testable live demo and at the same time the platform where I show my work. Originally created as a recruitment trial task, I have since continued to run it as my own demo, learning, and product project — on a Hetzner VPS behind a Cloudflare tunnel, through a multi-stage AI-orchestrated deploy pipeline with snapshot rollback. If a deploy step breaks, the system falls back to the last clean snapshot, the script is adjusted, the test repeated — empirical, test-driven, without hand tuning.
- Technically behind it: Python and FastAPI, an OpenRouter model cascade, SQLite persistence, and Cloudflare edge tuning.
- I am the developer and the strictest customer of my own AI work in one person — what started as a prototype has become a tool I use every day and against which I test my own products.
Dominic Dreiner
Last position:
Senior GEO Strategist & AI Search Consultant at Venmate GmbH
- Industry: SaaS (Customer Success Management) – B2B
Comprehensive GEO implementation (Generative Engine Optimization) for a B2B CSM SaaS startup with a focus on AI Search Visibility and AI Citations in ChatGPT, Perplexity and Google AI Overviews – including a GEO workshop and a prioritized implementation roadmap.
- GEO Workshop & Roadmap: Conceptualized and delivered a GEO workshop (how LLMs work, AI Search Architecture, citation strategies); translated it into a prioritized implementation roadmap with impact/effort estimates
- Technical GEO Foundation: Robots.txt & llms.txt, Core Web Vitals & page speed, XML sitemaps for AI crawlers
- Schema & Structured Data: Gap analysis, implementation of Product/Service, FAQ, Article, Author and Organization schema, validation of coverage
- Content Architecture & GEO: Flat content architecture, topic clusters (pillar-and-spoke), 200–300 word chunks and answer-first content structure, E-E-A-T rollout through author pages
- Query Fan-Out & Prompt Anticipation: User prompt mapping, query fan-out, content gap analysis based on prompt coverage
- Citation & Backlink Strategy: AI citation analysis (news, Reddit, Wikipedia, listicles) and development of outreach and backlink strategies
Tools & technologies: Otterly.AI, PeecAI, Qforia (iPullRank), Schema Markup Validator, OpenAI Tokenizer, Prompt Coverage Monitor, ChatGPT, Perplexity AI, Semrush, Ahrefs, Framer CMS
Alexander Schulze
Last position:
AI Consultant for AI Voice Bot System at Rudolf Hörmann GmbH & Co.KG
- Consultant for system architecture, AI agents & integration, coach for data & process logic, Graph-RAG approaches, security and data protection.
- On-premise AI solutions with high compliance and performance requirements.
- Architecture decisions, operational setup, strategic prioritization & deployment.
- Technologies: LiveKit JS SDK, LiveKit Agents, Web Audio API, JS, AudioWorklet, Loki, vLLM, Zscaler, Docker, Neo4j, MySQL, Python.
- Models: GPT-OSS 20B, Whisper large v3 turbo, Qwen3-TTS.
Jay Black
Last position:
Senior SEO Manager at CoachHub
- Developed and implemented data-driven SEO strategies aligning with business objectives.
- Continuously monitored and analyzed SEO metrics, optimizing online visibility and search rankings.
- Produced engaging and SEO-optimized content, enhancing the user experience.
- Implemented advanced technical SEO techniques for improved website structure and mobile-friendliness.
- Led outreach campaigns to secure high-quality backlinks, improving domain authority.
- Stayed current with the latest SEO trends, sharing knowledge with the team for a competitive edge.
Discover over 15,000 top freelancers
Statistics of experts using JSON-LD
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
1.3 years
Positions per freelancer
15
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Professional Services, Food and Beverage
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
40%
Certifications per freelancer
3
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Germany using JSON-LD
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Structured data
JSON-LD is a format for adding structured data to web pages and digital products. It is widely used with schema.org to describe products, articles, events, organizations, and local business details in a way machines can read reliably.
Where it fits
- Search engine rich results and knowledge panels
- Product, article, FAQ, and event markup
- Internal knowledge graphs and content feeds
- API payloads that need linked data structure
It is usually embedded in HTML as a script block, separate from visible page content and easier to maintain than inline microdata.
Skills around it
Strong specialists know JSON syntax, schema.org types, and how search crawlers interpret markup. They also understand canonical URLs, page templates, content models, and validation tools, so the data stays accurate when pages change.
When companies bring in help
Teams often need freelance expertise when launching a new site, fixing invalid markup, or scaling structured data across many templates. In Germany, this is common for e-commerce, publishing, travel, and event-heavy sites that need clean search presentation and stable content operations.
What good work looks like
A strong professional maps the right entity types to each page, avoids duplicate or conflicting properties, and tests the result in structured data tools. They work with editors, SEO specialists, and web teams to keep JSON-LD consistent after releases and content updates.
Common implementation tasks
- Design schema.org mapping for page types
- Add JSON-LD to templates and components
- Validate output after CMS or code changes
- Fix nesting, identifiers, and language fields
- Document rules for content teams and future updates
Frequently asked questions
What clients ask us most about JSON-LD — answered in short.
JSON-LD is used to describe page content in a machine-readable way, usually for search engines and other systems that need structured facts. It is common for product pages, articles, FAQs, events, organizations, and local business pages. The goal is clear interpretation, not visual design.
JSON-LD is usually easier to maintain because it sits in a separate script block instead of being woven through HTML tags. That makes it a better fit for teams that manage many templates or update content often. Microdata and RDFa can work too, but they are harder to edit cleanly at scale.
A strong JSON-LD specialist should also know schema.org, HTML templates, content management systems, and basic search engine behavior. On larger sites, they often need to understand content modeling and release workflows too. Validation and debugging skills matter just as much as writing the markup.
JSON-LD projects can be small or complex, depending on the site. A simple page template fix needs less depth than a full structured data rollout across a large catalog or multilingual site. The important part is proven work with the exact page types you use.
Yes, JSON-LD work is often remote because the markup is tied to pages, templates, and validation rather than physical presence. For teams in Germany, remote collaboration works well when the specialist can review content structure, SEO requirements, and release plans clearly. On-site sessions help when many stakeholders must agree on page models fast.
A good JSON-LD deliverable is valid, specific to the page type, and consistent with visible content. Look for correct entity types, stable identifiers, sensible nesting, and clean handling of language and variants. Good specialists also explain why each field is there.
No, JSON-LD is not only for SEO, even though search visibility is the most common reason teams adopt it. It is also useful anywhere systems need shared meaning, such as product feeds, internal catalogs, and knowledge graphs. The value is structured facts that can be reused.
Before starting JSON-LD work, freelancers should ask which page types need markup, which schema.org entities are approved, and how the site is built. They should also confirm who owns content changes and how validation will be handled after release. That avoids mismatches between code, content, and search requirements.
The average hourly rate of freelancers in Germany who have used JSON-LD in their recent projects is 90 €, which corresponds to a daily rate of about 720 € based on an 8-hour working day.
Of the freelancers in Germany who have used JSON-LD in their recent projects, 40% hold at least a Bachelor's degree.
On average, freelancers in Germany who have used JSON-LD in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 1.3 years.
The most common languages among freelancers in Germany who have used JSON-LD in their recent projects are German (100%), English (100%), and Spanish (33%).
The most common industries among freelancers in Germany who have used JSON-LD in their recent projects are Information Technology (100%), Professional Services (67%), and Food and Beverage (50%).
The most common business areas among freelancers in Germany who have used JSON-LD in their recent projects are Information Technology (83%), Product Development (83%), and Project Management (83%).
Main locations of FRATCH Experts, who have recently used JSON-LD
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
