Jakarta Persistence (JPA) Experts in Frankfurt
, matched fast with vetted, available freelancersHire experts who design entity models, tune Hibernate-based persistence and integrate JPA with Spring applications, REST services and transactional databases. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your project.
Meet FRATCH Experts in Frankfurt, who have recently used Jakarta Persistence (JPA)
Uday V.
Last position:
Senior Full Stack Java Developer & DevOps Engineer at Deutsche Börse (DBAG)
Project: SCS (Settlement / Clearing Services)
Settlement platform serving multiple trading and clearing venues — counterparty risk safeguarding, settlement volume reduction, central risk management, and post-trade anonymity.
Technologies: Java 17, Spring Boot 3, Microservices, Spring Data JPA, SonarQube, Fortify (SCST), Mockito, Jenkins, OpenShift, Maven, Podman, GitHub, JIRA, Liquibase, Swagger, AMQP, Apache Camel, Terraform, PostgreSQL, Instana, Graylog.
- Identified and remediated CVEs in third-party libraries using SCA tooling, strengthening the security posture of production components.
- Maintained 90% code coverage with SonarQube, improving code quality and reducing production defects.
- Enabled mTLS for database authentication and message broker connections, enforcing encrypted, certificate-validated communication.
- Designed and deployed microservices with asynchronous, REST-based communication between components.
- Optimized a high-volume REST API (~200K requests) by reducing response time from 3s to 2s (33% improvement), boosting throughput and reliability under production load.
- Automated build and continuous integration pipelines using Maven and Jenkins.
- Orchestrated containerized workloads on Podman/OpenShift and governed schema evolution with Liquibase, ensuring reliable, repeatable deployments across all environments.
- Optimized Java code and implemented EHCache-based caching, improving application performance.
- Streamlined release management by governing application images, JAR versions, and dependencies through DBAG Artifactory, ensuring version consistency and audit traceability across environments
David R.
Last position:
Lead Developer/Technical Architect
- Design, extension, and implementation of interfaces (REST, GraphQL, Kafka)
- Architecture and implementation of cloud-native microservices on Azure Kubernetes Service
- Domain-Driven Design, Event-Driven Architecture with Kafka
- Development of an extensive query engine for REST endpoints based on business objects
- Design and implementation of master data classification using machine learning algorithms (Weka library, Spotify Voyager)
- Analysis and evaluation of complex load test scenarios and derivation of optimizations
- Increase in system resilience (Kafka error handling, circuit breaker, sidecar service mesh in Go)
- Integration with CIAM systems (asynchronous real-time synchronization and definition of data ownership, authorization, authentication)
- Connection to Azure ServiceBus (AMQP protocol)
- Design and implementation of complex authorization concepts (including delegated administration)
- Documentation of the results (Confluence, architecture descriptions, architecture decisions)
Ralf K.
Last position:
Senior Java Developer, Consultant at Dataport AÖR
- Maintenance and further development of the Java/Swing-based @rtus FormsEditor
- Design and development of a graphical formula editor based on Google Blockly for representing a project-specific DSL, including parsing and code generation
- Implementation of character-accurate synchronization between the editor and print preview to improve the user experience
- Technologies: Java 17/21, Swing, JavaFX, JBoss/Wildfly, JUnit, Mockito, Blockly, JPedal, ICEPDF, Eclipse
Florian F.
Last position:
Senior Backend Developer at ING Deutschland AG
- Database design with Oracle DB, JPA and Flyway considering high performance requirements
- Analysis of multiple architecture drafts and identification of technical risks
- Design and implementation of various interfaces and integrations, especially REST APIs and Kafka topics
- Setup of Elasticsearch for monitoring and analyzing log data
- Establishment of an iterative work approach in the project team facing complex business requirements
Adil S.
Last position:
Mobile/Backend Developer at Freelance
- Built a cross-platform mobile application using React Native that interacts with IoT devices via RESTful APIs
- Implemented state management with Redux and integrated IoT-specific components for smooth data visualization and device control
- Developed RESTful APIs using Node.js and Express, utilizing MongoDB for scalable data storage
- Facilitated secure communication between the mobile app and IoT devices, enabling device onboarding, status monitoring, and control commands
- Implemented real-time data synchronization and optimized data flow to minimize latency
Rashid I.
Last position:
Java Developer at IT company
- Data transformations
- IT company with more than 100 employees
- Software production
- Data augmentation and normalization, image transformation, format conversion, merging data from multiple sources
- Toolset: Java, Helm, Kubernetes, Kafka, OpenCV, IntelliJ IDEA, Gradle, Git, Docker, Containers, Scrum
Jörg-Ulrich H.
Last position:
Data flows for health insurance providers
- Further development and creation of data flows for health insurance providers
- Data management across various storage systems (DB2, MSSQL, PostgreSQL, S3, custom APIs, ...)
- Documentation and training
- Planning and deployment of NiFi 2.x (major upgrade)
- Integrating Grafana for visualization, monitoring, and alerting
- Extensive use of the NiFi API to continuously monitor the system and its components
Gulam N.
Last position:
Full-Stack Developer at .Attendo
Developed Skalman’s Food & Sleep Clock web app with a digital assistant that reminds users about medication intake, meals, movement breaks, and other daily routines.
Implemented personalized meal suggestions and simple recipes with support for allergies and special diets, integrating AI to generate tailored meal ideas.
Built Flight Booking App using React and Axios for the front end, Spring Boot with JPA and MySQL for the back end, and implemented user authentication, form validation, and booking logic.
Designed and built a chatbot that accepts natural language queries and generates intelligent responses using OpenAI’s language model.
Developed MarketPlace_AP with React and Axios on the front end, Spring Boot with JPA and MySQL on the back end, enabling users to discover services or products, with authentication and form validation.
Created a Meeting Calendar page allowing users to schedule, view, and manage meetings using React, Axios, Spring Boot, JPA, MySQL, and authentication with validation.
Created a Todo List Manager: built a REST API with Node.js, Express, and MongoDB; developed a React front end featuring status toggling and filtering; deployed on Heroku and integrated with GitHub for CI/CD.
Ingo D.
Last position:
Analytics at BaFin - Federal Financial Supervisory Authority Frankfurt
- Introduction of approaches for developing and automatically deploying cloud-native software and machine learning programs in OpenShift clusters
- Development of various programs in Python
- Technologies: Kubernetes, OpenShift, Kustomize, ArgoCD, Tekton, Docker, PodMan, Airflow, IntelliJ, PyCharm, Git, Bitbucket, Jira, Confluence, Python
Discover over 15,000 top freelancers
Statistics of experts using Jakarta Persistence (JPA)
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
1.9 years (Germany: 2.1 years)
Positions per freelancer
15 (Germany: 14)
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
67% (Germany: 55%)
Doctorate
17% (Germany: 11%)
Certifications per freelancer
1 (Germany: 3)
Most common languages
German, English, Russian
Speak two or more languages
100% (Germany: 96%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Frankfurt 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 Frankfurt using Jakarta Persistence (JPA)
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Jakarta Persistence (JPA) 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 (78%)
- Automotive (56%)
- Telecommunication (56%)
- Transportation (44%)
- Tourism (44%)
- Energy (33%)
- Government and Administration (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What JPA does
Jakarta Persistence (JPA) is the standard Java specification for mapping application objects to relational database tables. It defines entities, relationships, persistence contexts, queries and transaction behavior, while implementations such as Hibernate provide the runtime engine. Teams use it to keep database access consistent across business applications.
Where it fits
JPA appears in enterprise services, customer portals, payment systems, inventory tools and internal applications that depend on structured relational data. It commonly runs with Jakarta EE, Spring, Spring Data JPA, REST APIs and databases such as PostgreSQL, MySQL or Oracle.
- Map entities and inheritance structures
- Model one-to-one, one-to-many and many-to-many relationships
- Implement JPQL, Criteria API and native queries
- Manage transactions, locking and caching
Ecosystem skills
Strong JPA work includes more than annotations. Specialists understand Hibernate behavior, schema design, JDBC, connection pools, transaction boundaries and migration tools such as Flyway or Liquibase. They also connect persistence decisions with Java application architecture, testing, security and observability.
When specialists help
Companies bring in freelance expertise when a new service needs a durable data model, an older persistence layer becomes difficult to maintain or production queries slow down. Support is also useful during migrations from older Java EE packages to Jakarta namespaces, database changes, performance reviews and integration work across distributed services.
- Review entity mappings and fetch plans
- Refactor repositories and persistence boundaries
- Diagnose N+1 queries, deadlocks and unexpected updates
- Create migration and rollback strategies
What good work looks like
Reliable professionals make persistence behavior explicit. They choose relationships carefully, avoid accidental eager loading, keep transactions at clear boundaries and test queries against realistic data. They can explain when JPQL, native SQL or a different data-access approach is the safer choice.
Collaboration in Frankfurt
A Frankfurt-based specialist can work on-site, remotely or in a blended team, depending on security requirements and delivery routines. Clear communication matters when persistence changes affect application, database and operations teams across locations. Look for evidence of maintainable entity models, measured query performance and disciplined release practices.
Frequently asked questions
Curious about Jakarta Persistence (JPA)? Here are the answers that come up again and again.
Jakarta Persistence (JPA) is used to map Java objects to relational database records and manage their lifecycle within application transactions. It provides common rules for entities, relationships and queries, while an implementation such as Hibernate performs the actual persistence work.
JPA reduces repetitive SQL and mapping code by representing database records as entities and relationships. JDBC offers finer control and can be preferable for highly specialized queries, but it requires more manual handling of result sets, transactions and object mapping.
Jakarta Persistence (JPA) is a specification, not a complete runtime product. Hibernate is a widely used implementation of that specification, so a project can use JPA concepts and APIs while relying on Hibernate-specific behavior where appropriate.
JPA work benefits from strong Java, SQL and relational database knowledge. A capable specialist should also understand Spring or Jakarta EE, transaction management, database migrations, testing, query profiling and the effect of persistence choices on REST or messaging services.
The right level depends on the scope, not a fixed number of years. Jakarta Persistence (JPA) work on a new service may need solid entity and transaction skills, while a legacy migration or performance investigation calls for experience with Hibernate internals, production diagnostics and database changes.
Jakarta Persistence (JPA) projects are often suitable for remote collaboration when the specialist can access secure development environments and database documentation. Frankfurt teams should agree on communication routines, review practices and language expectations before work begins; on-site sessions can help with complex architecture or compliance discussions.
Ask the specialist to explain entity ownership, fetch strategies, transaction boundaries and query behavior using a relevant example. Good JPA work includes focused tests, observable SQL, controlled schema changes and clear reasoning about when native SQL is safer than an abstraction.
Jakarta Persistence (JPA) may be a poor fit for workloads dominated by complex reporting SQL, bulk data processing or database-specific features that the abstraction obscures. A specialist should compare it with JDBC, jOOQ or direct SQL and recommend the approach that best matches query control, maintainability and performance needs.
The average hourly rate of freelancers in Frankfurt, Germany who have used Jakarta Persistence (JPA) in their recent projects is 90 €, which corresponds to a daily rate of about 724 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Jakarta Persistence (JPA) in their recent projects, 100% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Jakarta Persistence (JPA) in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Frankfurt, Germany who have used Jakarta Persistence (JPA) in their recent projects are German (100%), English (100%), and Russian (22%).
The most common industries among freelancers in Frankfurt, Germany who have used Jakarta Persistence (JPA) in their recent projects are Information Technology (100%), Banking and Finance (78%), and Automotive (56%).
The most common business areas among freelancers in Frankfurt, Germany who have used Jakarta Persistence (JPA) in their recent projects are Information Technology (100%), Product Development (100%), and Quality Assurance (67%).
Main locations of FRATCH Experts, who have recently used Jakarta Persistence (JPA)
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 
Stuttgart 
Dusseldorf Countries:
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