SPARQL Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used SPARQL
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
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.
Basem Elasioty
Last position:
Head of Cloud & AI at VxLabs GmbH
- Led cloud and data engineering organization, defining architecture strategy for next-generation data platforms
- Designed and delivered an automotive fleet data management system including scalable ingestion pipelines, signal catalog management, and campaign processing workflows
- Built cloud-native microservices and streaming architectures supporting real-time vehicle data and AI-powered threat detection
- Established engineering standards for data quality, security, lineage, and governance in alignment with ISO/SAE 21434 and GDPR
- Managed engineering teams across data, backend, cloud, and AI functions, ensuring consistent delivery of high-quality, production-ready solutions
Paul Oesterwitz
Last position:
Product Owner / Project Manager at Auditor, software vendor for German tax consultancies
- Project environment: Python, Java, Azure AI Studio & OpenAI Studio, embedding models, LLM as a judge
- Project language: German
- Project role(s): Project manager
- Project management for improving the performance of a chatbot
- Research and evaluation of approaches to improve and measure response accuracy and improve the chatbot's understanding of context
- Coordination of architecture decisions with the technical team and architects
- Coordination and transfer of research results into development tasks
André Ullmann
Last position:
RTE / Agile Coach / Full SAFe Consultant at Siemens Energy
- RTE/Agile Coach for the SAFe 6 (Scaled Agile Framework) rollout
- Building and establishing a LACE (Lean-Agile Center of Excellence) for several ARTs
- Using the tools: Azure DevOps with SCALE, Loop, MS Whiteboard
- Building the ART with 7 teams
- Training Product Owners, e.g. through SAFe POPM training and LearnSnacks
- Running the initial PI Planning as a Kickoff Planning Event
- Introducing a demand process
Younes Hadrous
Last position:
Senior Backend Developer at PTA
- Development and maintenance of database-driven applications for managing supplier and food contracts, using Oracle PL/SQL extensively for complex business logic and data processing
- Optimization of PL/SQL procedures, functions, and triggers to ensure the performance and scalability of Oracle database solutions
- Ensuring adherence to best practices in PL/SQL development and implementing standards for code quality and data integrity
- Close collaboration with backend and frontend teams to ensure seamless integration between the Oracle database, C#-based APIs, and Azure cloud services
Alishiba Florian Dsouza
Last position:
Research Assistant at University of Bonn
- Led data engineering and machine learning efforts for large-scale Knowledge Graph creation of WorldKG
- Developed pipelines for heterogeneous data integration (OpenStreetMap, Wikidata, DBpedia) using Python and SQL
- Designed neural architectures (Transformers, adversarial networks) for schema and entity alignment
- Created scalable ETL workflows to harmonize structured and unstructured geographic information
- Applied semantic modeling and SPARQL-based querying for data fusion and governance
- Mentored master’s students on AI, spatiotemporal data, and Knowledge Graph topics, fostering practical experimentation and innovation
Mario Ellebrecht
Last position:
Developer and Consultant at Freelancer
Discover over 15,000 top freelancers
Statistics of experts using SPARQL
Aggregated from the professional profiles of matched freelancers.
Experience
26 years
Position duration
2.3 years
Positions per freelancer
17
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Automotive, Education
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
83%
Master's degree or higher
83%
Doctorate
33%
Certifications per freelancer
8
Most common languages
German, English, Arabic
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 SPARQL
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
SPARQL in practice
SPARQL is the query language for RDF data. It is used to read, filter, join, and update graph-shaped information stored in triple stores and exposed through SPARQL endpoints.
What it is used for
- Knowledge graphs and semantic search
- Data integration across linked sources
- Ontology-driven reporting and discovery
- RDF data validation and updates
It appears in search, publishing, research, and master data work. In Germany, teams often use it where structured data must stay connected across systems and vocabularies.
Core ecosystem
Strong specialists work comfortably with RDF, RDFS, OWL, SHACL, and popular triple stores such as GraphDB, Apache Jena, Blazegraph, and Stardog. They also understand namespaces, prefixes, graph patterns, and how to read endpoint behavior.
When companies bring in help
Companies usually need freelance expertise when a SPARQL layer is slow, hard to maintain, or missing clear query standards. They also bring in support for migrations, endpoint design, ontology alignment, and query review before production release.
What good specialists do
Good professionals write clear queries, avoid unnecessary joins, and think in graphs rather than tables. They can debug blank results, shape reusable query templates, and explain tradeoffs between SPARQL, SQL, and application-side filtering.
Typical delivery work
- Query libraries and reusable patterns
- Endpoint access rules and documentation
- Data model reviews for RDF graphs
- Performance fixes for slow queries
On-site work can help with stakeholder workshops, but much SPARQL work is remote if the data access is well documented. For German teams, English is common in the technical stack, while local workshops may benefit from German-speaking specialists.
Frequently asked questions
Questions about SPARQL? Start with the answers below.
SPARQL is used to query RDF data and work with knowledge graphs. It helps teams join linked sources, retrieve facts from ontologies, and expose structured data through a SPARQL endpoint. Companies use it when relationships matter as much as records.
SPARQL works on graph data, while SQL is built for relational tables. SPARQL is better when the model contains many linked entities, changing vocabularies, or semantic relationships. SQL is usually simpler for fixed tables and standard reporting.
A strong SPARQL specialist usually knows RDF, OWL, SHACL, and graph modeling. Experience with triple stores, ontology design, and endpoint troubleshooting is valuable too. The best people can also explain how the data model affects query shape and performance.
A small reporting or query-review task may need only one experienced SPARQL professional. A larger knowledge graph program usually needs someone who can handle data modeling, query optimization, and stakeholder communication. The right level depends on how mature the RDF layer already is.
Yes, most SPARQL work can be handled remotely if the endpoint, sample data, and ontology documentation are available. For teams in Germany, remote collaboration is common for query work, but on-site sessions can help during modeling workshops or knowledge transfer.
If queries are slow, results are inconsistent, or nobody can explain the ontology behind the data, SPARQL help is overdue. The same applies when teams are building a new endpoint or migrating from a legacy RDF store. Clear query ownership is a good sign you need outside support.
Ask for examples of production SPARQL queries, endpoint tuning work, and RDF modeling decisions. Good answers should mention how they handle prefixes, blank nodes, graph patterns, and debugging empty result sets. You want evidence of clear thinking, not just syntax knowledge.
Yes, SPARQL remains central wherever RDF and semantic web data are in use. Newer graph tools may offer different APIs or query styles, but SPARQL is still the standard for many knowledge graph and linked data setups. Its value is strongest when interoperability matters.
The average hourly rate of freelancers in Germany who have used SPARQL in their recent projects is 100 €, which corresponds to a daily rate of about 798 € based on an 8-hour working day.
Of the freelancers in Germany who have used SPARQL in their recent projects, 83% hold at least a Bachelor's degree, 83% hold at least a Master's degree, and 33% hold a doctorate.
On average, freelancers in Germany who have used SPARQL in their recent projects have 26 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Germany who have used SPARQL in their recent projects are German (100%), English (100%), and Arabic (25%).
The most common industries among freelancers in Germany who have used SPARQL in their recent projects are Information Technology (100%), Automotive (63%), and Education (63%).
The most common business areas among freelancers in Germany who have used SPARQL in their recent projects are Information Technology (100%), Product Development (88%), and Project Management (75%).
Main locations of FRATCH Experts, who have recently used SPARQL
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
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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Philipp Thomaschewski
FRATCH CEO
