MongoDB Experts in Berlin
matched in minutes from over 15,000 CVsHire experts who design document models, build aggregation pipelines and connect MongoDB to modern applications. Get precise access to vetted, available freelancers who can support migrations, performance work and production delivery with speed.
Meet FRATCH Experts in Berlin, who have recently used MongoDB
William N.
Last position:
Power BI Solutions Architect/Engineer & AI Consultant at AVERDUNG GmbH
- Redesign of the company's BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment featuring a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic into a central semantic model – eliminating redundant files, manual data transfers, and inconsistent metrics between departments
- Forecasting & planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enables rolling forecasts and continuously up-to-date cash flow transparency for management
- Optimization of existing Power BI dashboards in terms of performance, structure, and analytical value using an AI-native approach
- Analysis and improvement of the data model, including data quality analyses, data cleansing, and consistent modeling using star schema, DAX, and Power Query
- Incident & anomaly analysis: Identification, investigation, and explanation of data anomalies, including root-cause analysis and concrete recommendations for action
- AI solution architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Creation of a historical data layer as a basis for trend and time-series analyses
- AI-supported automation: Design and development of AI skills, agents, loops, and processes for the automated analysis and interpretation of reports
- Automated reporting workflow: Setup of scheduled, automated email distribution of AI-generated analyses and recommendations to stakeholders
- Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
- Breaking down overall requirements into clearly defined work packages and tasks
- Definition, prioritization, and management of milestones throughout the entire project lifecycle
Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code
Sascha B.
Last position:
Web Developer at GxPlex
- Built a customized MediaWiki instance, including installation, MySQL database, SSL, and automatic backups
- Set up user roles (Admin, Mod, Verified, User) and a permissions system
- FlaggedRevisions for editorial review workflows · Commenting and rating extensions
Chintan P.
Last position:
Product Owner and Technical Product Lead at Sustamize GmbH
LLM-based features for automated CO₂e data extraction from unstructured documents (70% reduction)
Agentic AI pipeline for automated Scope 3 emissions calculations with 150.000+ validated data records
Intelligent API workflows for real-time carbon footprint calculations in ERP and ESG systems
ML algorithms for predicting emissions hotspots and optimizing product design
Automated data validation pipelines with NLP for quality assurance of CO₂e datasets
Led a 15-person cross-functional team in developing 10+ AI features
Strategic product planning and AI roadmap with 35% shorter time-to-market
Stakeholder management with DAX companies (40% higher satisfaction, 95% retention)
On-time project delivery with 95% budget adherence through data-driven backlog management
Agile methods (Scrum, Kanban) with continuous AI/ML integration (25% increase in team velocity)
Product-market fit for AI features through A/B testing and analytics (60% higher adoption rate)
Oleg A.
Last position:
Staff Software Engineer at Kpler Germany GmbH
- Delivered a new notifications platform implementation built from scratch to replace existing and upcoming services
- Collaborating with other teams to integrate more domains
Tech stack:
- Data: Scala 3, Apache Kafka, Python, Airflow, Astronomer
- BE-FE: TypeScript, NestJS, Java, Spring Boot, Vue
- Dev-ops: AWS, PostgreSQL, Docker, GitHub Actions, Kubernetes, Helm, ArgoCD
Saman S.
Last position:
AI Product Builder at Instalemon.com
- Architected and built an agentic creative automation platform on Mastra, with a custom RAG pipeline, custom hooks, tools and skills, Chroma for vector storage, and a MongoDB/Express backend.
- Built the agent orchestration layer powering Pixomi's multi-agent workspace, including 72 custom marketing skills, tools and hooks, and a custom context-management pipeline.
- Designed and implemented evals and observability through Mastra studio.
- Onboarded 10 pilot SMB customers producing 10x publish-ready creative output per campaign versus manual production in 3 months.
- Ran customer discovery and pilot feedback loops to shape the roadmap for an AI-native, workflow-based creation platform.
Rüdiger S.
Last position:
Full-Stack Software Engineer / Consultant for Digitalization at ARTEVENT
Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.
Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.
Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.
Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.
Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.
Jorge P.
Last position:
Software Engineer – AWS and Kubernetes Specialist at Citti
- Creation, maintenance and hardening of Kubernetes clusters employing Ansible and ArgoCD
- Keywords: Ansible, AWX, Kubernetes, NetApp, Prometheus, CI/CD ArgoCD, SSO, Fluent-bit, HAProxy, Calico, Keycloak, oauth2-proxy, SealedSecrets, kubeseal, Aqua kube-bench, CIS-Benchmarks, Aqua Trivy operator
Aruldass A.
Last position:
Web Module Lead at Mphasis Limited
- Led the end-to-end delivery of enterprise full-stack web applications by driving requirement analysis, solution design, frontend and backend development, database design, API integration, code reviews, team coordination, Agile execution, CI/CD deployments, production support, performance optimization, security implementation, and stakeholder collaboration to deliver scalable, high-quality software solutions.
Santhosh K.
Last position:
Freelance Software Engineer at Zalando SE
- Drive migration of enterprise authorization platform from Styra DAS to open-source OPA via Skipper (Zalando's Golang-based ingress proxy) integration
- Optimise k8s resources and integrate native Prometheus metrics with OPA
- Migrate from internal monitoring solution to Prometheus CRs + Dash0
Tech Stack: Java/Kotlin, Golang, Python, Spring Boot, AWS, Kubernetes, Docker, OpenTofu, Prometheus, Grafana
Maciej R.
Last position:
Full Stack Developer (Freelancer) at Runbuggy
- Led development of RunBot AI assistant autonomously using LLM-powered workflow automation (React, TypeScript, Java, MongoDB, NATS)
- Architected TMS platform providing unified transportation management and real-time logistics visibility with AI processing pipelines
- Designed event-driven microservices architecture supporting marketplace
- Drove architectural decisions and technical leadership across full-stack platform development
Imran A.
Last position:
Software Engineer II at LivePerson Germany GmbH
- Led development of 15+ microservices (Java 17, Spring Boot) driving customer interactions; migrated from on-prem to GCP Kubernetes, improving scalability and reducing infra cost by 20%.
- Optimized user services with CouchDB caching and API refactoring, cutting response times by 35% and enhancing customer experience.
- Implemented canary deployments, FluxCD GitOps, and CI/CD optimizations in GitLab, reducing release lead time by 25% and enabling zero-downtime rollouts.
- Set up Grafana health checks and Anodot alerts for latency, error, and throughput monitoring, reducing MTTR by 40%.
- Built secure APIs using OAuth2, DPoP, and Gatekeeper, integrated REST and GraphQL, and achieved 90%+ test coverage with unit and E2E tests.
- Mentored junior developers, promoted Agile best practices, and collaborated cross-functionally to deliver high-impact, reliable customer-facing features.
Wolfram K.
Last position:
AI / Machine Learning Engineer (Projects & Applied AI) at UNIVERSITÉ PARIS 1 PANTHEON-SORBONNE & LIORA
- Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
- Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
- Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
- Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
- Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow
Muzamal A.
Last position:
Data Scientist / AI Consultant at HelmX
- Delivered AI and data science solutions, including LLM-based chatbots and data pipelines, improving operational efficiency.
- Collaborated on product features, achieving measurable impact and maintaining strong client relationships.
Nune I.
Last position:
Fractional CTO at OpsWorker
OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.
Raphael M.
Last position:
Founder / Quant Developer at Market Maker
- Crypto quant strategy development, automated trade execution, onchain data client (Ethereum / Solana)
- Data and trade architecture development for liquidity provision
Discover over 15,000 top freelancers
Statistics of experts using MongoDB
Aggregated from the professional profiles of matched freelancers.
Experience
15 years (Germany: 17 years)
Position duration
2.1 years
Positions per freelancer
9 (Germany: 11)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Retail
Certification focus areas
Information Technology, Product Development, Business Intelligence
Bachelor's degree or higher
98% (Germany: 92%)
Master's degree or higher
67% (Germany: 57%)
Doctorate
6%
Certifications per freelancer
2
Most common languages
English, German, French
Speak two or more languages
95% (Germany: 97%)
Based on our profile pool as of 9 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Berlin are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Berlin using MongoDB
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 9 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
MongoDB experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (95%)
- Banking and Finance (43%)
- Retail (38%)
- Automotive (37%)
- Education (33%)
- Media and Entertainment (30%)
- Professional Services (29%)
- Healthcare (25%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Document database foundations
MongoDB is a document-oriented NoSQL database built around flexible BSON documents rather than fixed relational rows. It suits applications that handle changing data structures, nested records and rapid product iteration. Teams use it for operational data, content, customer profiles, catalogs and event-driven services.
Data models and queries
Strong MongoDB specialists translate application needs into clear collections, embedded documents and references. They create indexes, validation rules and aggregation pipelines that keep reads predictable as data grows. They also select read and write concerns carefully when consistency, availability and latency must be balanced.
Ecosystem and tooling
MongoDB work often spans more than the database itself:
- MongoDB Atlas deployment, networking and access control
- Aggregation pipelines, change streams and transactions
- Drivers for Node.js, Java, Python, Go or .NET
- Backup, restore, monitoring and schema analysis
Professionals may also work with Kafka, Kubernetes, Docker, Redis and cloud services around the data layer.
Where companies use it
MongoDB supports product platforms, APIs, mobile back ends, marketplaces, media systems and internal tools. Its document model is useful when records contain varied attributes or when teams need to evolve features without repeated table redesign. It can also serve as part of a polyglot persistence architecture alongside relational databases.
When freelance expertise helps
Companies bring in specialists when an existing deployment has slow queries, unclear schemas or rising operational risk. They also seek outside support for migrations, Atlas setup, sharding decisions, security reviews and production recovery planning. In Berlin, remote delivery is common, while workshops may require on-site collaboration and clear English or German communication.
What strong specialists deliver
A capable MongoDB professional links database choices to application behavior and business needs. They explain trade-offs between MongoDB, PostgreSQL and other NoSQL systems instead of treating one tool as universal. Look for practical evidence: tested migration plans, useful observability, documented indexes, automated backups and clear runbooks for the team that will operate the system.
Frequently asked questions
What clients ask us most about MongoDB — answered in short.
MongoDB is commonly used for APIs, content platforms, product catalogs, customer data and applications with varied or evolving records. Its document model keeps related information together and can reduce friction when features change.
MongoDB uses flexible documents, while PostgreSQL is a relational database with strong table-based structure and SQL capabilities. The better choice depends on relationships, transaction requirements, query patterns and the team’s operating model rather than on a general claim that one is faster.
A strong MongoDB specialist should understand application drivers, data modeling, indexing and production monitoring. Cloud deployment with MongoDB Atlas, containerization, backup design and experience with services such as Kafka or Kubernetes are also useful for broader projects.
The right level depends on the scope. A simple application may need a specialist who can model collections and tune queries, while a production migration or sharded environment calls for proven experience with availability, recovery, security and operational testing.
Yes. MongoDB projects are often handled remotely through shared repositories, observability tools, documented decisions and secure access procedures. Berlin-based teams may still prefer on-site workshops for architecture reviews, incident preparation or close collaboration with product and application specialists.
MongoDB Atlas can be a practical choice when a team wants managed provisioning, monitoring, backups and security features around its database service. The decision should still account for network design, data residency needs, operational controls and the skills available to run the application.
Ask a MongoDB expert to explain a real data model, the indexes behind important queries and how they validated performance. Good answers include trade-offs, failure handling, backup recovery tests and documentation that another specialist can operate.
MongoDB can represent relationships through references, embedded documents and application logic, but it may be less natural when many entities require complex joins and strict relational constraints. A specialist should compare the access patterns with PostgreSQL or another relational option before recommending the database.
The average hourly rate of freelancers in Berlin, Germany who have used MongoDB in their recent projects is 84 €, which corresponds to a daily rate of about 670 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used MongoDB in their recent projects, 98% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 6% hold a doctorate.
On average, freelancers in Berlin, Germany who have used MongoDB in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 2.1 years.
The most common languages among freelancers in Berlin, Germany who have used MongoDB in their recent projects are English (99%), German (94%), and French (10%).
The most common industries among freelancers in Berlin, Germany who have used MongoDB in their recent projects are Information Technology (95%), Banking and Finance (43%), and Retail (38%).
The most common business areas among freelancers in Berlin, Germany who have used MongoDB in their recent projects are Information Technology (99%), Product Development (96%), and Business Intelligence (48%).
Main locations of FRATCH Experts, who have recently used MongoDB
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.
Hamburg 
Munich 
Cologne 
Frankfurt 
Stuttgart 
Dusseldorf 
Leipzig 
Dortmund 
Essen 
Nuremberg Request a free demo
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FRATCH CEO
