
NoSQL Expert
in minutes from over 15,000 CVs with the power of AIHire experts who design document, key-value, wide-column and graph data solutions, optimize MongoDB or Cassandra workloads, and connect NoSQL stores with modern applications. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts who have recently used NoSQL
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 using a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic in a central semantic model – elimination of redundant files, manual data transfers and inconsistent metrics across 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; enabling 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 specific recommendations for action
- AI Solution Architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Development 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 delivery 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
Dany-Armand D.
Last position:
Senior Data Scientist at ibg NDT GmbH
- Investigate the relationship between Eddy Current Testing (ECT) signals and microstructural properties
- Detect latent patterns in ECT data that reflect intrinsic material characteristics
- Develop and validate predictive models for microstructural classification and quantification, using hardness and case depth as benchmarks
- Apply Bayesian Structural Equation Modeling for advanced data analysis
Reinhold M.
Last position:
Business Requirements Engineer, Proxy Product Owner, Tester at AXA Konzern AG
Working Environment
- Insurance / Claims Management (Property, Liability, Automotive)
- REST-based ClaimAPI with Guidewire ClaimCenter
Scope
- Further development of the internal REST-based ClaimAPI with Guidewire ClaimCenter as the backend and various portals/front-end offices as clients, and with the following objectives: + increased AI-supported claims processing outside of Guidewire ClaimCenter + and support for all lines (property, liability, automotive).
- Further development of automated claims processing
Activities
- Interfacing IT & Business
- Design activities with documentation in Confluence, Jira: + Requirements engineering (functional and non-functional) + Design of REST endpoints and coordination with interface partners (esp. AI-colleagues) + Identification, design and evaluation of alternative solutions (moving away from a monolithic approach toward fine-grained endpoints, with code reuse across all lines if possible) + Creation / refinement of product backlog items in Jira, i.e. epics, user stories and tasks, incl. alignment with developers & POs during (pre-)refinement sessions + Using AXA Secure GPT when creating / refining user stories (description, acceptance criteria) and designing REST endpoints + Estimation and prioritization of user stories and tasks during Sprint Planning sessions + Coordination and support during the implementation of Product Backlog items + Driving decision making with preparation and presentation of decision-making documents
- Quality assurance: + Test management, including test case creation using Xray in Jira + Test execution using Bruno as REST client and in Guidewire ClaimCenter + Submission of test artifacts for PO approval + Analysis of production bugs
Methods Big Room Planning (aka PI-Planning in SAFe), Scrum, BPMN, EPK, UML, ERM, DDD
Tools / Tech Stack Teams, Confluence, Jira with Xray, OpenAPI/Swagger, REST, JSON, XML, MS Office, Bruno, GitHub repository (reading), Guidewire ClaimCenter, AXA Secure GPT (AXA's in-house GenAI solution based on Azure OpenAI)
Paul W.
Last position:
Enterprise Architect at ePrimo GmbH
Led the end-to-end integration and migration architecture for decommissioning SAP IS-U market communication and transitioning to Salesforce Marketing Cloud (SFMC) with E.ON IT Services — covering regulated EDIFACT market messaging, a three-phase data migration (transfer of market message inventory after cutover), redesign of market communication processes, and full GDPR and German energy-market compliance.
- Designed the three-tier target architecture (SAP IS-U → NScale B2B gateway → SFMC) processing 50,000–100,000 EDIFACT messages daily within sub-5-minute SLAs.
- Architected the three-phase data migration: 36 months of historical data, zero-loss cutover of in-flight market messages, and near-real-time CDC synchronization.
- Delivered secure, BDEW/GDPR-compliant integration (AS2/OFTP2, RFC/IDoc, REST APIs, OAuth 2.0, Azure AD, AWS S3) achieving >99.5% uptime, <0.1% migration discrepancy, and RTO <4 hours.
- Applied BPMN to model and optimize the market communication processes.
Technologies: SAP IS-U, NScale, Salesforce Marketing Cloud, EDIFACT, OAuth 2.0, Azure AD, AWS S3, BPMN, Jira, Confluence, Draw.io
Vaios K.
Last position:
Product Manager & Strategic Advisor at Freelance, Lovable, Dreamarium
- Advise early-stage startups on product vision, roadmapping, and GTM strategy, combining PMP and Stanford PM training with hands-on technical execution.
- Lovable: built and led a 200+ member community program for AI-native founders, bridging real-time founder feedback into product roadmap decisions.
- Lead customer discovery and OKR design engagements, scoping AI integration opportunities across client products.
Niko S.
Last position:
Developing Architect, Technical Lead "gridlytics" at HH Energienetze
- Built a data integration platform for high-, medium- and low-voltage assets to enable contextual analysis of time series with master data from SCADA control systems (IEC 60870 104), INIS and SAP.
- Responsible for the architecture and implementation of the solution, and acted as a sparring partner for the Product Owner.
- Technologies used: Kotlin, Spring Boot, Maven, TimescaleDB, PostgreSQL, liquibase, Elements IoT, Docker, Kubernetes, Grafana, Python, jupyter and various API gateways.
Umut G.
Last position:
Data Architect at BA Technology
I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.
I delivered following projects and engagements as a freelancer.
- Data Migration of CRM System for AL-FA Objekt Service Gmbh
- Microsoft Software Resales Partnership
I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer
Technical Focus Areas
- Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
- DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
- Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
- MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
- Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.
Carlos M.
Last position:
Implementation in Pimcore/Shopware
- Consulting, design, analysis, software architecture and development
- Design, development and implementation of a Pimcore environment and connection of several external API systems in a Kubernetes environment, as well as various PIM and ERP systems
- Technologies: Unix environment, design, Symfony development, design, PHP 8+, software architecture, MySQL/SQL, Shell Script, Git Dev Ops tasks, AI coding assistance, Pimcore 12, Shopware 6
- Team size: >10 people
Will O.
Last position:
Solution Architect at Polizei Behörde Stuttgart
Designed a migration strategy for WLS applications to BKA Cloud and Stack IT
Created a hybrid cloud for internal testing and development with Kubernetes
Transformed the IT landscape from an outdated monolithic architecture to a cloud-based architecture
Integrated new CI/CD processes using Azure Pipelines
Quadrupled the processing throughput for personnel security checks
Migrated personnel security screening applications to Docker-based applications
Implemented CI/deployment pipelines using Azure DevOps
Environment: Java Springboot, Kubernetes, Oracle Weblogic, OpenID, Camunda, JUnit, TOGAF
Mirza K.
Last position:
Agentic Automation and a RAG system
- This project involved extraction of intelligence data to support report writing for a company that provides geopolitical, global, commercial intelligence. The data have been gathered from a number of resources (interview transcripts, online data, internal documents), and then a knowledge base has been build from it. This was the basis of a complex RAG system, that was evaluated against a golden dataset. Agents have been used to find out the contradicting intelligence, the statements supporting each other, and to store back the generated knowledge.
Used: Python, RAG, LangGraph, LangChain, deepeval, MCP
Ramazan C.
Last position:
Fullstack-/DevOps Engineer at BKA (Federal Criminal Police Office)
Development and further development of an internal platform for managing and providing technical resources, virtual machines, and infrastructure services. The platform supports self-service processes and covers functions that are conceptually comparable to cloud management solutions like Azure or AWS.
- Responsible involvement in the design, development, and implementation of new backend and frontend features
- Hands-on development with Java, Spring Boot, Python, and Angular
- Implementation of REST interfaces, business logic, validations, and integrations into existing system landscapes
- Further development of modern web interfaces with Angular, including connection to backend services
- Participation in architecture and design decisions within the team, especially with regard to scalability, maintainability, and clean interfaces
- Containerization and deployment of applications with Docker, Kubernetes, and Helm
- Support with CI/CD processes and deployment to Kubernetes-based environments
- Work in the environment of vSphere, Broadcom, GitLab CI/CD, ArgoCD, Maven, npm, and NuGet
- Close collaboration with developers, business teams, DevOps, and other technical stakeholders
- Analysis of technical requirements, deriving suitable solutions, and independent implementation in an agile team
- Use of GitHub Copilot to support code generation, refactoring, test case creation, and technical documentation
Methods/ tools/ technologies: Languages & frameworks: Java (21), Spring Boot (4.x), Python, Angular, Robot Framework, Kubernetes, Helm Persistence: PostgreSQL, MongoDB, Hibernate, Liquibase Architecture & communication: REST, gRPC, GraphQL, Apache Kafka, OpenAPI, Microservices, Event Driven, Domain Driven Design Cloud & infrastructure: Terraform, Docker, Rancher, Helm, Ansible Security: OAuth2, MS (Entra ID), web security, Keycloak (extensions for detailed group rights) DevOps: GitLab CI/CD, Ansible, Maven, Gradle, Grafana, Prometheus, Git, GitHub Copilot Testing & QM: JUnit, Robot Framework, automated component and integration tests, E2E tests with Playwright, Testcontainers, EasyMock Methodology & approach: Kanban, JIRA, Confluence, Clean Code
Sascha W.
Last position:
Lead Product Owner CADKit at Ottobock SE
- Repositioned and provided functional leadership for a CAD web platform to digitally transform the prosthetics manufacturing process worldwide
- Translated the CPO vision into a technical roadmap and guided an interdisciplinary team of developers, designers, and QA specialists
- Delivered complex 3D interfaces based on Vue.js and Three.js
- Rolled out 8 scalable web apps worldwide, increasing production efficiency by 80%
Gwen G.
Last position:
Senior Ruby on Rails & DevOps Developer at Sapiens
Further development of a software solution for managing audit applications and audit notifications according to §106d SGB V for the Association of Statutory Health Insurance Physicians in Hamburg.
- Developed numerous features, optimised performance, refactored code and analysed errors
- Refactored the development container setup
- Optimised the Gitlab-CI build pipeline
- Introduced improvements to the team workflow
Sabahattin K.
Last position:
Sole responsibility (design, development, infrastructure, operations) at Own project busik.ch
- Ride-sharing and bus platform, live and fully functional. Backend with Spring Boot 4.1 on Java 21, PostgreSQL with Flyway, and Testcontainers integration tests. Hosted 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 fully AI-supported with Claude Code, including custom skills and project-specific memory. Spring Boot · Java 21 · PostgreSQL · Flyway · Docker · AWS ECS/ALB/ECR · CI/CD · GitHub Actions · Claude Code
Caleb C.
Last position:
Senior Python Backend Engineer at Simon-Kucher
Transmission system operator – network provisioning platform (team lead)
- Designed the saga orchestrator in Python that provisions network fabrics with rollback.
- Split IP, identity, and resource allocation into bounded contexts with their own databases and typed clients.
- Implemented data access using DDD repositories and units of work, with no SQL in the domain code.
- Required integration tests using real PostgreSQL and RabbitMQ containers, and API fuzzing for every service.
- Introduced an agent workflow where a spec starts each change and a human approves every merge.
- Rolled out OpenTelemetry auto-instrumentation through GitOps across eighteen Kubernetes clusters.
- Led incident response for stuck provisioning and recorded every outage as a post-mortem.
Languages and software used: Python, FastAPI, Pydantic v2, SQLAlchemy async, PostgreSQL, RabbitMQ, Celery, pytest, testcontainers, schemathesis, Helm, Flux CD, GitLab CI, OpenTelemetry, pi coding agent.
Software product company – datacenter simulation SaaS (backend development)
- Built the asynchronous simulation pipeline as the second-largest contributor among more than twenty team members.
- Tagged every image by commit SHA and semver in the GitHub Actions deployment workflows.
- Diagnosed the RabbitMQ memory alarm that froze every simulation and fixed the limits in the Helm chart.
- Converted the test suite to function-style pytest, with coverage reported in every pipeline.
Languages and software used: Python, FastAPI, SQLAlchemy, Alembic, Celery, RabbitMQ, Redis, PostgreSQL, S3, EKS, Helm, Keycloak, GitHub Actions, pytest, mypy, ruff, SonarQube.
Internal AI platform – model serving and telemetry
- Built the FastAPI service that deploys open-weight models on GPU tiers as OpenAI-compatible endpoints.
- Upgraded production EKS by two Kubernetes minor versions and fixed zone-bound storage faults.
- Traced every model call, including its token count, cost, and latency, through the OpenTelemetry operator.
Languages and software used: Python, FastAPI, vLLM, LangGraph, pydantic-ai, OpenAI and Anthropic APIs, EKS, Helm, Flux CD, Terraform, GitLab CI, OpenTelemetry, Grafana.
Discover over 15,000 top freelancers
Statistics of experts using NoSQL
Aggregated from the professional profiles of matched freelancers.
Experience
17 years

Position duration
5.2 years

Positions per freelancer
12

Top business areas
Information Technology, Product Development, Quality Assurance

Top industries
Information Technology, Banking and Finance, Manufacturing

Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
91%
Master's degree or higher
57%
Doctorate
10%

Certifications per freelancer
2

Most common languages
English, German, French

Speak two or more languages
98%
Based on our profile pool as of 5 Nov 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology 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 using NoSQL
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 5 Nov 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
NoSQL 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 (92%)
- Banking and Finance (44%)
- Manufacturing (40%)
- Retail (38%)
- Automotive (36%)
- Education (36%)
- Professional Services (34%)
- Healthcare (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What NoSQL covers
NoSQL is a group of database technologies built for data that does not fit neatly into fixed relational tables. Document, key-value, wide-column and graph databases support flexible schemas, high-throughput workloads and distributed operation. Common names include MongoDB, Redis, Cassandra, DynamoDB and Neo4j.
Where it fits
NoSQL stores support products and services that need fast access, flexible data models or large volumes of changing records.
- Real-time applications, mobile back ends and content platforms
- Product catalogs, user profiles and session management
- Event streams, telemetry and recommendation features
- Social graphs, knowledge graphs and relationship analysis
Ecosystem and tooling
Strong NoSQL specialists work across database engines, application services and cloud infrastructure. Their toolkit may include MongoDB Atlas, Redis, Amazon DynamoDB, Apache Cassandra, Couchbase, Neo4j, Kafka and Kubernetes. They also use drivers, SDKs, migration tools, observability systems and infrastructure as code.
When companies need expertise
Companies often bring in freelance NoSQL expertise during a new product build, a migration from SQL, a scaling effort or a reliability problem. Specialist support is useful when teams must choose a data model, plan partitioning, control storage costs or recover from inefficient queries.
- A relational schema is slowing feature delivery
- Traffic patterns or data volume are changing quickly
- Replication, failover or consistency needs review
- A cloud database requires secure production setup
What the work includes
A NoSQL professional can model documents, keys, columns or graph relationships; configure indexes and partition strategies; and build reliable data access layers. Deliverables may include migration plans, schema conventions, backup procedures, performance tests, monitoring dashboards and runbooks. Good work connects database choices to product behavior instead of treating the store in isolation.
What strong specialists show
Look for practical knowledge of consistency models, replication, sharding, indexing, transactions and data lifecycle management. Strong specialists explain when SQL is the better choice and when NoSQL provides a clear benefit. They test failure scenarios, document trade-offs and make operational risks visible before production traffic exposes them.
Frequently asked questions
Need clarity? These are the questions we hear most often about NoSQL.
NoSQL is used for flexible, distributed data storage in applications such as content platforms, real-time services, catalogs, event systems and graph-based products. The right database type depends on access patterns, consistency needs and how the data changes.
NoSQL databases often prioritize flexible schemas, horizontal scaling or specialized access patterns, while relational databases provide structured tables, joins and mature transaction models. A good specialist evaluates the workload rather than assuming one approach is always superior.
A NoSQL choice should follow the data model and workload. MongoDB suits document-oriented applications, Redis supports fast in-memory access, Cassandra handles distributed wide-column workloads, DynamoDB provides managed key-value and document storage, and Neo4j focuses on connected data.
A strong NoSQL freelancer should understand application architecture, cloud services, data migration, observability and security. Experience with APIs, event streaming, containers and infrastructure automation is also valuable for production systems.
The required depth depends on the risk and scope of the work. A specialist handling schema design, migration, partitioning or failover should have proven experience with the chosen database and with production operations, not only application-level usage.
NoSQL work is well suited to remote collaboration when documentation, access controls and observability are in place. Teams should agree on communication routines, incident ownership and the language used for technical decisions before work begins.
Ask a NoSQL specialist to explain data-model decisions, consistency trade-offs, failure handling and query performance in plain language. Review relevant architecture samples, migration plans or runbooks, and look for evidence of testing under realistic load.
NoSQL may be a poor fit when the system depends on complex joins, strict relational integrity or broad ad hoc reporting. A capable specialist will say when a relational database, search engine or combination of systems better matches the requirements.
The average hourly rate of freelancers who have used NoSQL in their recent projects is 93 €, which corresponds to a daily rate of about 745 € based on an 8-hour working day.
Of the freelancers who have used NoSQL in their recent projects, 91% hold at least a Bachelor's degree, 57% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers who have used NoSQL in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 5.2 years.
The most common languages among freelancers who have used NoSQL in their recent projects are English (98%), German (96%), and French (17%).
The most common industries among freelancers who have used NoSQL in their recent projects are Information Technology (92%), Banking and Finance (44%), and Manufacturing (40%).
The most common business areas among freelancers who have used NoSQL in their recent projects are Information Technology (98%), Product Development (89%), and Quality Assurance (45%).
Main locations of FRATCH Experts, who have recently used NoSQL
Our freelancers and interim experts are at home all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Across Switzerland our specialists are active in Zurich, Geneva, Basel and Bern — working on-site or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Countries:
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