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MongoDB Experts

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Hire experts who design document models, tune queries and indexes, and build reliable MongoDB Atlas setups. Get fast, precise matching with vetted, available freelancers.

Meet FRATCH Experts who have recently used MongoDB

Verified expert

Sascha Bach

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Accessibility, Creativity and Innovation for Businesses

Berlin
Sascha Bach

Last position:

Freelance at GxPlex

  • Built a custom 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 workflow · comment and rating extensions
Verified expert

Ales Loncar

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Senior DevOps Consultant (Freelance)

Munich
Ales Loncar

Last position:

Senior DevOps Consultant (Freelance) at European Union Agency (via IBM)

  • Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
  • Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
  • Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
  • Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
  • Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
  • Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
  • Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
  • Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
  • Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
  • Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.
Verified expert

Karen Manukyan

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Senior .NET Backend Engineer | Applied AI | Agentic Systems, RAG & Distributed Architecture

Munich
Karen Manukyan

Last position:

Personal AI Engineering Project — Croky AI at Crocky AI

Product:

  • Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
  • Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
  • Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
  • Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
  • Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.

Agent Orchestration & RAG Systems

  • Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
  • Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.
Verified expert

Karin Albiez

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Language Expert – Python Developer – AI Engineer

Leonberg
Karin Albiez

Last position:

AI Benchmark Engineer | Native language specialist German at Lilt

  • Task Engineering: Evaluating Coding Agents.
  • Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
  • Prompting & Translation: finding failure points where AI does not work, in German.
  • Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
  • Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
  • Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
  • Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.
Verified expert

Marijn Scholtens

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Cloud Solutions Architect or Senior Software Engineer

Düsseldorf
Marijn Scholtens

Last position:

Senior Software Engineer at Puls Security GmbH

  • Optimizing and accelera­tion of our Gitlab CI pipeline

  • Conceptual work for the PoC of the Zero Trust system

  • Extension of the policy-engine backend in Go

  • Extension of the policy-testing mechanism in Python

  • Architectural design of the PEP component of Zero Trust

  • Documentation of the product

  • Technologies: Zero Trust, Go, Python, Gitlab CI, Docker, JWT, Domain-Driven Design

Verified expert

Niko Schmuck

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Developing Architect / Solution Architect

Hamburg
Niko Schmuck

Last position:

Developing Architect, Technical Lead "gridlytics" at HH Energienetze

  • Building a data integration platform for high, medium, and low voltage assets for contextual analysis of time series with master data from the SCADA control system (IEC 60870 104), INIS, and SAP.
  • Responsibility for the architecture and implementation of the solution, as well as sparring partner for the Product Owner.
  • Use of Kotlin, Spring Boot, Maven, TimescaleDB, PostgreSQL, liquibase, Elements IoT, Docker, Kubernetes, Grafana, Python, jupyter, and various API gateways.
Verified expert

Priyanka Sarang

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Business Consultant (Software Engineering)

Hanover
Priyanka Sarang

Last position:

Business Consultant (Software Engineering) at Boehringer Ingelheim

  • Developed cloud-native enterprise applications on SAP Business Technology Platform using Node.js, SAP UI5, and RESTful APIs, delivering solutions across training management, procurement, employee information, and logistics domains
  • Served as the primary developer for the maintenance, enhancement, and production support of three enterprise applications, delivering new features, resolving production issues, and coordinating releases with business stakeholders
  • Experienced in leveraging AI-assisted development tools such as Microsoft Copilot to accelerate feature development, generate code, prototype solutions, and support application migration and modernization
  • Designed backend services, domain models, and SAP Fiori/UI5 interfaces, implementing business workflows, role-based access control, validations, scheduling, reporting, and data import/export capabilities
  • Designed and integrated enterprise services with SAP SuccessFactors, SailPoint, ERP systems, and external Learning Management APIs, including automated synchronization for 11,000+ user data
  • Designed and implemented AMQP-based event-driven services processing up to 500 RFID parcel scan events per day for a logistics application
  • Managed deployments and application operations using CI/CD pipelines, SAP Solution Manager, SAP BTP Cockpit, Kibana, and cloud monitoring tools, performing root-cause analysis and resolving production incidents
  • Managed application dependencies by resolving npm package version conflicts and remediating critical and high-severity security vulnerabilities, ensuring production compliance and application stability
  • Collaborated with architects, business users, SAP governance teams, and distributed Agile teams throughout technical design, code reviews, sprint planning, documentation, and software delivery
Verified expert

Chintan Padaliya

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Product Owner and Technical Product Lead

Berlin
Chintan Padaliya

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 calculation with 150,000+ validated data records

  • Smart API workflows for real-time carbon footprint calculations in ERP and ESG systems

  • ML algorithms to predict emission hotspots and optimize product design

  • Automated data validation pipelines with NLP for quality assurance of CO₂e datasets

  • Led a 15-person cross-functional team to develop 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% team velocity increase)

  • Product-market fit for AI features through A/B testing and analytics (60% higher adoption rate)

Verified expert

Yusuf Congar

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Senior Software Engineer C# | C++ | Java | JS | Microservices | Vert.x | OSGI | IoT | Hardware | MQTT

Würselen
Yusuf Congar

Last position:

Senior Software Engineer at LeiKon GmbH

  • Development of scalable backend applications with C#/.NET and Java
  • Design and implementation of distributed microservice architectures
  • Development and integration of REST APIs for industrial applications
  • Development of modern web applications with React, Angular, and TypeScript
  • Implementation of MQTT-based communication solutions
  • Integration of industrial protocols such as OPC UA and Modbus TCP
  • Development of batch, process control, and HMI components
  • Containerization and deployment of applications with Docker
  • Conducting code reviews and supporting architecture decisions
  • Close collaboration with product owners, QA, and interdisciplinary teams
  • Analysis of business requirements and implementation of technical solutions
  • Further development of existing software architectures with a focus on maintainability and performance

Technologies: C#, .NET, ASP.NET Core, Java, C++, React, Angular, TypeScript, Vue.JS, MQTT, OPC UA, Modbus TCP, Docker, GitLab, MariaDB, MySQL, Linux

Verified expert

Sabahattin Kunas

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Senior Java Developer | Lead Developer | Architect | Team Lead

Diedorf
Sabahattin Kunas

Last position:

Fully responsible (concept, development, infrastructure, operations) at Own project busik.ch

  • Ride-sharing and bus platform, live and fully functional. Backend Spring Boot 4.1 on Java 21, PostgreSQL with Flyway, Testcontainers integration tests. Operation in my own AWS account (ECS Fargate, ALB, ECR, IAM least privilege) with CI/CD via GitHub Actions and OIDC federation without static credentials. Development throughout AI-assisted with Claude Code, including my own skills and project-specific memory. Spring Boot · Java 21 · PostgreSQL · Flyway · Docker · AWS ECS/ALB/ECR · CI/CD · GitHub Actions · Claude Code
Verified expert

Christian Frauer

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IT Project Implementer (Problem Solver)

Buxtehude
Christian Frauer

Last position:

Department Head (Interim) at Municipal utility and transport company

  • Definition and setup of the subject areas
  • Building a governance model for the department with the areas of responsibility
  • IT strategy, project management, process management, and quality and sustainability management
  • Developing a communication strategy for the group
  • Creating an IT strategy
  • Designing templates, guidelines, and processes for standardized work
  • Capturing strategic guardrails and grouping ongoing projects – deriving a roadmap for strategic planning
  • Reviewing ongoing projects
  • Creating staffing and capacity calculations
  • Defining job profiles
Verified expert

Boris Solos

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Senior Software Developer

Ratingen
Boris Solos

Last position:

Generalist expert for software development at Mercor

  • Training AI models, evaluating images and text UI/UX, turning the provided data into insights through OpenAI Feather as part of the machine learning workflow

Technologies: OpenAI Feather

Verified expert

Ali Aminian

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Enterprise Software Architect | Cloud, Integration & AI Platforms

Frankfurt
Ali Aminian

Last position:

Platform Engineer & Software Architect at Yatta GmbH

  • Architected the Yatta Integration Layer – a config-driven integration platform on Java 25, Spring Boot 4 (WebFlux), Temporal, gRPC and Kafka, enabling new third-party integrations (e.g. AVS fulfillment) via declarative JSON configs with zero code changes.
  • Designed and implemented Tink integration with 0Auth IBAN verification to enhance fraud prevention and account validation workflows with Adyen payByBank.
  • Architected and implemented an OpenFGA-based authorization model for centralized management of users, groups, and fine-grained access control in the vendor portal.
  • Architected and led delivery of the Yatta API Gateway platform using GraphQL Federation, providing a unified enterprise API layer across distributed microservices with centralized authentication, authorization and request orchestration.
  • Replaced NGINX + NLB with Istio service mesh and AWS ALB; rolled out WAF, OAuth (Cognito), IP whitelisting and RBAC across environments.
  • Migrated CDC from Confluent Cloud connectors to a self-hosted Kafka Connect + Debezium stack, reducing operational cost by ~80% across multiple environments.
  • Implemented the Transactional Outbox pattern with Debezium for reliable, exactly-once event publishing to Kafka with Avro and Schema Registry.
  • Migrated dunning/payment-recovery workflows from Airflow to Temporal, achieving 99.9% reliability for settlement handling.
  • Optimised Apache Airflow with deferrable sensors to handle 1000+ concurrent DAG runs without scaling the worker pool.
  • Refactored a monolithic Terraform codebase into 3 modular projects, cutting deployment time by ~45%.
  • Stood up full observability with OpenTelemetry, Tempo, Prometheus and Loki; automated dev/staging/prod with ArgoCD, Image Updater and Helm.
  • Collaborated with product, operations and engineering stakeholders to define scalable platform architecture and integration standards aligned with long-term business and operational goals.
Verified expert

Niklas Witzel

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Senior IT Consultant

Eichenzell
Niklas Witzel

Last position:

AI Engineer at Tensora GmbH

  • Designed and developed a multi-tenant SaaS platform enabling organizations to build their own knowledge bases and chat with brand-customized AI assistants (white-label approach with dynamic branding per organization).
  • Implemented a scalable RAG architecture with a GPT-4o tool-use loop, hybrid semantic search, and strict tenant isolation at database and search index level.
  • Built persistent, project-like chat sessions including a streaming API (SSE), multilingual support, and speech input/output (STT/TTS).
  • Delivered the cloud infrastructure as Infrastructure-as-Code, fully automated per-customer CI/CD pipelines, and an onboarding process for new tenants.

Technologies used: Python, FastAPI, Pydantic (v2 noted), Next.js, React, TypeScript, Tailwind CSS, OpenAI / LLMs (GPT-4o), Azure AI Search, Cosmos DB, Azure Blob Storage, Azure Cognitive Services Speech, Azure App Service, Azure Container Registry, Retrieval-Augmented Generation (RAG), Server-Sent Events (SSE), Docker, Terraform, GitHub Actions, REST, OpenID Connect (OIDC), Multi-Tenancy

Discover over 15,000 top freelancers

Statistics of experts using MongoDB

Aggregated from the professional profiles of matched freelancers.

Experience

17 years

Position duration

2.1 years

Positions per freelancer

11

Top business areas

Information Technology, Product Development, Quality Assurance

Top industries

Information Technology, Banking and Finance, Retail

Certification focus areas

Information Technology, Product Development, Project Management

Bachelor's degree or higher

93%

Master's degree or higher

57%

Doctorate

6%

Certifications per freelancer

2

Most common languages

English, German, French

Speak two or more languages

97%

Based on our profile pool as of 6 Sep 2026.

Daily rate distribution

0 60 120 180 240
<€400 €400-​800 €800-​1200 €1200-​1600 €1600+

The chart shows how the daily rates of freelancers in this technology 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 using MongoDB

Rates are based on recent contracts and do not include FRATCH margin.

800
600
400
200
Rate comparison chart
Daily rate avg. 740 €

The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.

800
600
400
200
Rate comparison chart
Median rate 720 €

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 6 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.

About the technology

Document model

MongoDB stores data as flexible documents instead of fixed rows and columns. That makes it a strong fit for product catalogs, content systems, event data, profiles, and APIs that change often. Companies bring in specialists when they need to model data cleanly before growth turns small mistakes into hard-to-fix issues.

Querying

Good MongoDB work is not only about saving JSON-like documents. It also includes aggregation pipelines, indexes, data validation, and careful query design so applications stay fast and predictable.

  • Query tuning and index design
  • Aggregation pipelines for reporting and transformations
  • Schema validation and data shape reviews
  • Read and write path troubleshooting

Atlas and operations

Many teams use MongoDB Atlas for managed clusters, backups, alerts, and scaling. Specialists help with cluster setup, replica sets, sharding, security rules, and routine maintenance. They also spot issues around slow queries, storage growth, and connection handling before they affect production.

When to hire

Freelance expertise is useful when a team is starting a new product, refactoring an existing schema, or recovering from performance problems. It is also common during cloud migrations, release hardening, and audits of database access patterns.

  • New MongoDB or Mongo setup
  • Performance bottlenecks and index gaps
  • Migration from another database model
  • Production incidents and reliability work

What strong specialists bring

Strong MongoDB professionals think in access patterns, not just data storage. They understand how application code, indexes, replication, and backups affect each other, and they can explain trade-offs clearly to product and engineering teams. They also know when a document model is the right choice and when another store fits better.

Delivery in teams

MongoDB work often sits close to backend services, search, analytics, and infrastructure. In many cases the specialist can work remotely, review schemas, and pair with local teams in the same time zone. For regulated systems or sensitive environments, on-site collaboration may help during design reviews and production changes.

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Frequently asked questions

Need clarity? These are the questions we hear most often about MongoDB.

MongoDB is used for applications that need flexible data structures, fast iteration, and easy scaling. Teams use it for catalogs, user profiles, content systems, event tracking, and APIs that do not fit rigid tables well. It is especially useful when document shape changes over time.

MongoDB is usually chosen when document-first modeling matters more than strict relational structure. PostgreSQL and MySQL are often better when joins, constraints, and highly structured transactions are the core of the system. A good specialist will help you decide whether MongoDB or a relational database fits the workload.

MongoDB is the main product name, while Mongo is a common shorthand that still appears in searches. MongoDB Atlas matters when you use the managed cloud service and need help with cluster setup, backups, scaling, or security. The right freelancer should understand both the database itself and the Atlas operational layer.

A strong MongoDB specialist usually works comfortably with backend APIs, data modeling, indexing, aggregation, and cloud infrastructure. Depending on the project, knowledge of Node.js, Java, Python, or event-driven systems can also help. For production work, security and observability skills matter as well.

MongoDB projects can be simple at first, but experience becomes important as data volume, query complexity, and uptime expectations grow. If you only need a quick prototype, lighter support may be enough. For schema design, performance tuning, or production migrations, choose a specialist with clear delivery examples in similar environments.

Yes, MongoDB work is often remote-friendly because most tasks are schema design, query review, cluster configuration, or code collaboration. Remote support works well when communication is clear and access is properly managed. On-site time is mainly useful for sensitive production changes, workshops, or cross-team alignment.

A good MongoDB expert asks about access patterns, growth, backups, and failure scenarios before touching the schema. They should explain why an index is needed, when to denormalize, and how to keep reads and writes stable. Look for practical reasoning, not just familiarity with the name.

MongoDB is a strong option when you want flexible documents, rich querying, and a mature operational toolset. If your use case is key-value access, wide-column storage, or very specialized search, another NoSQL system may fit better. The best choice depends on data shape, query patterns, and how your application will grow.

The average hourly rate of freelancers who have used MongoDB in their recent projects is 93 €, which corresponds to a daily rate of about 740 € based on an 8-hour working day.

Of the freelancers who have used MongoDB in their recent projects, 93% hold at least a Bachelor's degree, 57% hold at least a Master's degree, and 6% hold a doctorate.

On average, freelancers who have used MongoDB in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 2.1 years.

The most common languages among freelancers who have used MongoDB in their recent projects are English (97%), German (97%), and French (15%).

The most common industries among freelancers who have used MongoDB in their recent projects are Information Technology (97%), Banking and Finance (46%), and Retail (40%).

The most common business areas among freelancers who have used MongoDB in their recent projects are Information Technology (99%), Product Development (93%), and Quality Assurance (50%).

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.

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