Spring Data Experts in Munich
for reliable data access, matched in minutes with vetted and available freelancersHire experts who design repository layers, connect Spring applications to relational and NoSQL databases, and tune persistence with JPA, MongoDB or JDBC. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Spring Data
Fred H.
Last position:
Software Architect and Developer at Personal project
Recurring problem in my own AI-assisted projects: requirements analysis, use cases, and architecture decisions can be created quickly with AI support, but remain difficult to follow 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 form a consistently linked knowledge graph, traceable from requirement to architecture decision – queryable by both people and AI agents. Technically based on RDF/OWL and a custom MCP server.
Result: Working MCP daemon, Docker image published automatically to GHCR, nine hexagonal modules, eleven ADRs (including an Open-Core licensing model). Requirements engineering and Ubiquitous Language hexagons are active. Public as a Community Edition under Apache-2.0 since 07/2026 (github.com/kogn-io/arknet), together with the Claude Code plugin and 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, Interface Development, Software Architecture, Continuous Integration, Knowledge Management
Christian T.
Last position:
HDI DevOps & Fullstack Engineer at HDI
- Spring Boot Software Engineer
- DevOps Engineer (Kubernetes, Azure DevOps)
Toolstack: Java, Spring Boot, Kubernetes, Helm, GitOps, ArgoCD, Docker, Azure DevOps, CI/CD Pipelines, Git, Postgres
Enis S.
Last position:
Software Developer at 50Hertz Transmission GmbH
- Participated in the gradual modernization of components into cloud-native 12-factor applications.
- Worked closely with the business operations team to eliminate manual processes and resolve several performance bottlenecks.
- Designed and implemented a CI/CD pipeline to increase developer productivity, enforce quality and security checks, and automate product delivery.
- Migrated several components into the OpenShift Kubernetes cluster.
- Built a monitoring stack from scratch with Prometheus and Grafana to monitor services running in OpenShift.
- Developed dashboards in both Grafana and Splunk for operational transparency.
- Implemented an OIDC/OAuth2-based single sign-on (SSO) solution with Keycloak to secure multiple applications.
- Technologies: Java, Spring, Quarkus, Kafka, MySQL, Cassandra, Redis, Spring Data, Hibernate, Docker, Kubernetes, OpenShift, Keycloak, OIDC, OAuth2, Helm, Prometheus, Grafana, Splunk, Spark.
Maryam N.
Last position:
Senior FullStack Developer at Camunda
- Role: Senior FullStack Developer
- Technologies: Google Cloud, Azure, Microsoft Entra, Keycloak, Spring Boot, Java
- Active in production
Dmitry V.
Last position:
Fullstack Software Developer at Mercedes-Benz Tech Innovation
- Backend development of the cloud-based microservice
- Frontend development of the microfrontend
- Migration of the cloud backend environment
- Rollout of the distributed high-availability Privacy Data Service
- Technologies: Java, Kotlin, Spring Boot, REST Services, Kubernetes, Microsoft Azure, Cloud Security, OpenAPI, Postman, JavaScript, Vue.js, AngularJS, TypeScript, Micro Frontend, Redis, Kibana, Grafana, CI/CD, GitHub Actions, Jenkins, Helm Charts, Sec-Hub, Black Duck, Docker, Maven, Git, Scrum
Benedikt B.
Last position:
Fullstack Developer at Nimevio
- Requirements analysis and planning of the software architecture
- Analysis and design of REST APIs
- Backend development with Java 17, Spring Boot, Spring MVC, and Spring Data
- Frontend development with Angular and TypeScript
- Setting up CI/CD pipelines
- Code review, QA, and testing
- Using MySQL, Docker, the ELK stack, and RabbitMQ
Bela B.
Last position:
Full Stack Lead Developer, Backend Architect at Telefonica (O2)
The software supports the complete planning and approval of antennas for mobile telephony.
The system was implemented using an event-driven microservice architecture for cloud-native deployment with Quarkus on the backend, Kafka for communication, and Angular for the frontend. Services run on Kubernetes in Google Cloud. A special challenge was synchronizing with the legacy system still used by some users.
Janusz M.
Last position:
IoT Edge Computing / Self-Driving-Cars at Automotive consulting company
- Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
- Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
- Responsible for webinar:
- IoT edge computing: architecture, components, resources, management
- IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
- IoT processes, connectivity, data transfer and deployment, security
- Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
- Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
- Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
- Analysis of large sensor data sets with Apache Spark, Kafka clusters
- Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
- Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
- Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))
Rangel S.
Last position:
Senior Software Consultant at Freelancer
Discover over 15,000 top freelancers
Statistics of experts using Spring Data
Aggregated from the professional profiles of matched freelancers.
Experience
24 years
Position duration
2.5 years
Positions per freelancer
13
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
100%
Master's degree or higher
100%
Doctorate
33%
Certifications per freelancer
1
Most common languages
German, English, Bulgarian
Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Munich 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 Munich using Spring Data
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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Spring Data 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 (100%)
- Banking and Finance (89%)
- Automotive (44%)
- Government and Administration (44%)
- Telecommunication (44%)
- Insurance (33%)
- Manufacturing (33%)
- Media and Entertainment (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Spring Data Does
Spring Data is a family of Spring projects that simplifies access to data stores through consistent repository patterns and familiar abstractions. It reduces repetitive persistence code while leaving room for store-specific queries, transactions and performance controls. Teams use it in services, APIs and enterprise applications built on the Spring ecosystem.
Supported Data Stores
The ecosystem covers relational and non-relational technologies, each with its own module and capabilities. Common project work includes:
- Spring Data JPA with Hibernate for relational persistence
- Spring Data JDBC for direct, simpler database access
- Spring Data MongoDB for document-oriented applications
- Spring Data Redis for caching, sessions and fast key-value access
- Spring Data Elasticsearch for search and indexing workflows
Skills Around the Framework
Strong professionals understand more than repository interfaces. They work with domain modelling, entity relationships, pagination, projections, query derivation, custom queries and transaction boundaries. Useful adjacent skills include Spring Boot, SQL, Hibernate, database migration tools, testing, observability and API design.
When Companies Need Expertise
Companies often bring in freelance specialists when a new Spring service needs a sound persistence layer or when an existing application suffers from slow queries, tangled repositories or unreliable transactions. They can also support database migrations, modularisation and the move between relational and document-based storage.
- Review persistence design and data access boundaries
- Improve query behaviour and loading strategies
- Establish tests for repositories and database integrations
What Professionals Deliver
Typical deliverables include a repository architecture, entity and aggregate mappings, migration scripts, integration tests and documented query conventions. Depending on the store, the work may also cover indexing, connection pools, caching, auditing and resilience. The result should be clear to maintain and aligned with the application’s consistency and performance needs.
How to Assess Quality
Look for professionals who can explain why a repository abstraction fits the use case and where it should not be used. Review examples involving transaction handling, query plans, schema evolution and production troubleshooting rather than interfaces alone. For teams in Munich, remote collaboration can work well when documentation, decision records and communication in the required team language are agreed early.
Frequently asked questions
Everything clients usually want to know about Spring Data, in one place.
Spring Data is used to connect Spring applications with databases and other data stores through consistent repository and query patterns. It supports relational systems, document databases, search engines, key-value stores and more, while allowing access to store-specific features.
Spring Data JPA builds on the JPA standard and commonly uses Hibernate underneath, adding repository interfaces, query derivation and integration with Spring transactions. Direct Hibernate gives lower-level control, while Spring Data JPA can reduce routine persistence code and establish consistent conventions.
A strong Spring Data specialist should understand Spring Boot, Java, SQL, JPA, Hibernate and database migration practices. Experience with testing, API design, transaction boundaries, indexing and observability is also valuable for production work.
The right Spring Data professional depends on the project’s data model, risk and operational complexity, not on a fixed experience label. Simple repository work may need focused framework knowledge, while migrations, performance issues and distributed transactions call for deep database and system design skills.
Spring Data supports both SQL and NoSQL through separate modules such as Spring Data JPA, Spring Data JDBC, Spring Data MongoDB and Spring Data Redis. The abstractions are familiar across modules, but modelling, consistency, querying and indexing still need to reflect each store’s behaviour.
Yes, Spring Data work is often suitable for remote collaboration because repository design, code review, testing and documentation can be handled online. Munich teams should define working hours, access to development databases and communication or language expectations before the engagement begins.
Ask a Spring Data professional to explain trade-offs around entity mappings, lazy loading, transactions, query performance and schema changes. A quality review should include tests, migration safety, database behaviour and maintainability rather than focusing only on repository interface syntax.
Spring Data may be a poor fit when an application needs highly specialised database operations, fine-grained control over generated SQL or a data model that does not map well to its repository abstractions. In those cases, direct JDBC, jOOQ, native database clients or store-specific APIs may offer better control.
The average hourly rate of freelancers in Munich, Germany who have used Spring Data in their recent projects is 97 €, which corresponds to a daily rate of about 772 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Spring Data in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 33% hold a doctorate.
On average, freelancers in Munich, Germany who have used Spring Data in their recent projects have 24 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers in Munich, Germany who have used Spring Data in their recent projects are German (100%), English (89%), and Bulgarian (11%).
The most common industries among freelancers in Munich, Germany who have used Spring Data in their recent projects are Information Technology (100%), Banking and Finance (89%), and Automotive (44%).
The most common business areas among freelancers in Munich, Germany who have used Spring Data in their recent projects are Information Technology (100%), Product Development (100%), and Project Management (56%).
Main locations of FRATCH Experts, who have recently used Spring Data
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.
Countries:
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
