ArangoDB Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used ArangoDB
Boris Solos
Last position:
Generalist expert for software development at Mercor
- Training the AI models, evaluating images and texts for UI/UX, turning the provided data into insights via OpenAI Feather as part of the machine learning workflow
Technologies: OpenAI Feather
Anthony Mugwang'a
Last position:
CodeValdCortex - Enterprise Multi-Agent AI Orchestration Platform at Personal Project
- Enterprise-grade multi-agent AI orchestration platform built with Go and Kubernetes for scalable, secure agent coordination in cloud-native environments.
- Multi-agent orchestration with intelligent workload distribution and dynamic scaling.
- Cloud-native architecture with Kubernetes deployment and horizontal auto-scaling.
- Real-time coordination with sub-100ms agent communication using Go channels.
- Enterprise security with zero-trust architecture, RBAC, and comprehensive audit trails.
- Visual workflow engine with monitoring, observability, and API gateway integration.
- Technologies: Go, Kubernetes, ArangoDB, gRPC, Prometheus, Grafana.
Sebastian Striebig
Last position:
Group Product Manager – Digital Platform Discovery at SPREAD.AI
- Developed and implemented organization-wide discovery framework based on Ulwick’s Outcome-Driven Innovation; enabled 7 Product Owners to systematically identify and quantify unrealized value through shared outcome language and opportunity scoring methodology
- Transformed Product Owner role from backlog clerks to strategic experimenters; established dedicated time budget for autonomous hypothesis testing and discovery activities
- Rebuilt customer journey maps to start at actual user need (tool selection phase) instead of platform entry point; eliminated manual data aggregation work previously done by project teams
- Implemented OKR framework across 4 product teams; defined quarterly objectives with measurable key results (e.g., 40% reduction in manual integration effort, self-service adoption increase)
- Unified 3 separate platform roadmaps through cross-team dependency mapping and shared service agreements
- Supported enterprise sales cycle with ROI modeling and technical due diligence for automotive and defense customers
Mohamed Ghassen Brahim
Last position:
Lead / Principal Cloud, AI & Security Architect at Freelancer / CC Conceptualise GmbH
Projects:
Project: RWE – Development of a company-wide Zero Trust cybersecurity architecture (CITADEL) Role: Senior Enterprise Cybersecurity Architect / Zero Trust Architect Company: RWE AG Description: Concept and implementation of the strategic CITADEL cybersecurity target architecture at RWE, based on the Zero Trust architecture principle and aligned with regulatory requirements such as NIS2, ISO 27001 and company-wide security governance policies. The goal was to build a measurable, auditable and scalable security architecture with a strong focus on Identity Governance, compliance transparency and operational manageability. Responsibilities & Achievements:
- Zero Trust architecture design: Developed a company-wide Zero Trust reference architecture (Identity, Device, Network, Application, Data) including trust zones, control points and enforcement mechanisms according to NIS2.
- Identity & Access Governance (IGA): Designed and introduced IGA governance structures including role models, recertification processes, segregation of duties (SoD) and lifecycle management for identities and access.
- Security governance & KPIs: Defined and implemented security KPIs and metrics to manage Zero Trust maturity, identity risks and compliance at the management level.
- Compliance & reporting: Built standardized compliance reports and dashboards to support internal audits, external assessments and regulatory evidence (e.g. NIS2).
- Architecture & stakeholder alignment: Worked closely with Enterprise Architecture, IT operations and business units to integrate the CITADEL architecture into existing IT and security landscapes.
- Strategic security consulting: Advised programs and projects on Zero Trust compliance, identity centricity and regulatory requirements in the energy and critical infrastructure (KRITIS) environment. Technologies & Methods: Zero Trust Architecture, NIS2, Identity Governance & Administration (IGA), IAM, RBAC, SoD, Entra ID, SailPoint, Zscaler, Terraform / IaC, Policy as Code, security KPIs, compliance reporting, NIST 2.0, ISO 27001, Enterprise Security Architecture, governance frameworks, risk & control management
Project: Scalable AI Workbench Platform on Microsoft Azure Role: Cloud Architect & Engineer Company: Siemens Energy Description: Design, development and operation of a secure, modular cloud infrastructure to support Data Science, Machine Learning and AI applications for various engineering teams at Siemens Energy. Responsibilities & Achievements:
- Cloud architecture: Designed and implemented an Infrastructure-as-Code solution (Terraform) for automated provisioning of Azure resources (Resource Groups, Storage Accounts, Cosmos DB, Application Insights, networking, PostgreSQL Flexible Server, Azure Container Apps, Azure Container Registry).
- Developer portal: Used Backstage with custom frontend and backend plugins (Node.js, TypeScript, React.js, PostgreSQL, Container Apps) to enable self-service and empower developers, data scientists and AI/ML engineers.
- Role-based access control: Implemented Azure RBAC to grant targeted access (e.g. Storage Blob Data Contributor, Reader) to engineering groups (e.g. AI Engineers) for relevant resources.
- Data platform engineering: Built and configured a multi-layered storage landscape (Raw, Curated, Vector data), including automated container creation and access control for advanced analytics and AI workloads.
- DevOps integration: Integrated with Azure DevOps for CI/CD pipelines to automate deployment, monitoring and compliance.
- Security & compliance: Implemented Private Endpoints, network policies and Managed Identities to ensure data protection and regulatory compliance.
- Collaboration: Worked closely with cross-functional teams to align the cloud infrastructure with business and technical requirements and drive digital transformation at Siemens Energy. Technologies: Azure, Terraform, Azure DevOps, Cosmos DB, Application Insights, Azure Storage, Private Endpoints, Azure Synapse, Azure Machine Learning, Azure Entra ID, RBAC, Backstage, Node.js, React.js, PostgreSQL, Python (automation), Git
Dawit Mulie
Last position:
Frontend Engineer at AIR GmbH
- Revamped frontend architecture from Svelte 4 to Svelte 5 elevating performance and maintainability
- Executed pixel-perfect Figma UI rollouts and redesigns embedding providers like M&M for frictionless insurance workflows
- Engineered robust Playwright E2E tests with Page Object Model tightly integrated with Azure CI/CD for bulletproof automation
- Spearheaded localization and internationalization across key modules enabling global scalability
- Orchestrated Azure PaaS migration (App Services, SQL, pipelines) and contributed to ERP/SAP system integrations
Andreas Jung
Last position:
Team Lead at Enquos.com
Discover over 15,000 top freelancers
Statistics of experts using ArangoDB
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
3 years
Positions per freelancer
8
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Business Intelligence, Legal
Bachelor's degree or higher
100%
Master's degree or higher
83%
Certifications per freelancer
4
Most common languages
English, German, Russian
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 ArangoDB
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
What it is
ArangoDB is a multi-model database used for document, graph, and key-value data in one system. Teams choose it when they need flexible data modeling without splitting core data across separate products. It is common in products that mix relationships, content, and fast lookups.
Where it fits
- Graph-heavy applications with connected data
- Product catalogs, profiles, and content stores
- Search-driven internal tools and APIs
- Systems that need one database for several access patterns
ArangoDB often appears in platform back ends, digital products, and data services where relationships matter as much as records.
Core skills
Strong professionals understand AQL, the query language for ArangoDB, and how to model data for joins, traversals, and document access. They also know indexing, sharding, replication, and how to keep query plans efficient. Experience with the ArangoDB ecosystem, including Foxx services and driver support, is a plus.
Typical work
- Design collection structures and graph models
- Write and optimize AQL queries
- Build APIs that read and write ArangoDB data
- Tune indexes, replication, and cluster setup
- Review migrations from MongoDB, Neo4j, or SQL-based designs
When to bring in help
Companies bring in freelance specialists when a data model feels forced, queries slow down, or a migration needs careful planning. In Germany, this is often useful for product teams that need focused support without long hiring cycles. Remote work is common, but on-site sessions help when the team wants deep architecture reviews or hands-on tuning.
What good professionals deliver
Good ArangoDB experts think in relationships first, not just tables or collections. They can explain trade-offs clearly, keep schemas practical, and write queries that are readable and maintainable. They also test failure cases, monitor performance, and leave the team with clear guidance for future changes.
Frequently asked questions
Quick answers to the questions that come up most around ArangoDB.
ArangoDB is used for systems that need documents, graphs, and simple key-value access in one database. It is a strong fit for connected data, product relationships, recommendation logic, and applications where one model is not enough. Teams also use it when they want to simplify their stack without losing flexibility.
ArangoDB is often chosen when a project needs document storage and graph traversal together. Compared with MongoDB, it adds native graph capabilities; compared with Neo4j, it gives teams document and graph models in one place. The best choice depends on whether your core work is records, relationships, or both.
A strong ArangoDB specialist should know AQL, indexing, data modeling, and cluster basics. They should also understand how to structure traversals, avoid expensive queries, and design data that matches the way the application reads and writes. API work and driver knowledge are common strengths too.
Projects need senior-level ArangoDB help when the first model no longer fits the product, when queries slow down, or when a migration becomes risky. That is also true for clustered setups, multi-tenant systems, and applications with complex relationship logic. A good specialist can spot design issues early and reduce rework.
Most ArangoDB work can be done remotely because schema design, AQL review, and performance tuning fit well into async collaboration. On-site time helps when the team needs a shared architecture workshop or wants to align several stakeholders quickly. In Germany, many teams use a hybrid setup for this kind of work.
Ask the ArangoDB freelancer which data models they have built, how they approach query optimization, and whether they have worked with clusters or migrations. You should also ask how they document schema decisions and how they test performance changes. Clear answers here usually reveal real depth.
Yes, ArangoDB is often used when search-like access and graph traversals need to live close together. That makes it useful for catalogs, content discovery, identity relationships, and internal tools. The key is designing indexes and queries so the system stays predictable.
The clearest sign is when the data model no longer matches the application and every new feature feels harder than it should. Another warning is a growing number of slow AQL queries or confusion about how collections relate to each other. At that point, an ArangoDB specialist can usually clean up the design and stabilize delivery.
The average hourly rate of freelancers in Germany who have used ArangoDB in their recent projects is 98 €, which corresponds to a daily rate of about 787 € based on an 8-hour working day.
Of the freelancers in Germany who have used ArangoDB in their recent projects, 100% hold at least a Bachelor's degree and 83% hold at least a Master's degree.
On average, freelancers in Germany who have used ArangoDB in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Germany who have used ArangoDB in their recent projects are English (100%), German (83%), and Russian (33%).
The most common industries among freelancers in Germany who have used ArangoDB in their recent projects are Information Technology (100%), Banking and Finance (67%), and Automotive (50%).
The most common business areas among freelancers in Germany who have used ArangoDB in their recent projects are Information Technology (100%), Product Development (83%), and Quality Assurance (83%).
Main locations of FRATCH Experts, who have recently used ArangoDB
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
