Jakarta Persistence (JPA) Experts in Frankfurt
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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
Ingo D.
Last position:
Analytics at BaFin - Federal Financial Supervisory Authority Frankfurt
- Introduction of methods for developing and automated deployment of cloud-native software and machine learning applications 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
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
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)
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
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 to map a project-specific DSL, including parsing and code generation
- Implementation of pixel-perfect synchronization between editor and print preview to improve user experience
- Technologies: Java 17/21, Swing, JavaFX, JBoss/Wildfly, JUnit, Mockito, Blockly, JPedal, ICEPDF, Eclipse
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.
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 years)
Positions per freelancer
15 (Germany: 13)
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: 10%)
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 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Frankfurt 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 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 19 Sep 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 Jakarta Persistence does
Jakarta Persistence (JPA) is the standard Java specification for mapping objects to relational database records. It defines entities, relationships, queries and transaction behavior so application code can work with domain models instead of hand-written SQL for every operation. The specification was formerly known as Java Persistence API.
Where it is used
JPA appears in business applications that need durable, structured data and clear domain relationships:
- Customer, account and order management systems
- Finance, insurance and supply chain applications
- REST services backed by relational databases
- Enterprise workflows with transactions and audit data
Hibernate is the most common implementation, while EclipseLink and OpenJPA are also used. Strong specialists understand the difference between the JPA contract and provider-specific features, including Hibernate annotations, fetching options and batch behavior.
Ecosystem and tooling
Effective work with Jakarta Persistence usually involves Java, Jakarta EE or Spring, and a relational database such as PostgreSQL, Oracle Database or Microsoft SQL Server. Professionals also use JPQL, Criteria API and native queries, alongside schema migration tools such as Flyway or Liquibase. Familiarity with Maven or Gradle, REST boundaries, transactions and automated tests helps keep the persistence layer maintainable.
When companies need expertise
Freelance expertise is useful when a team is introducing a persistence layer, modernizing an older Java application or dealing with slow and unreliable database access. Typical assignments include:
- Converting JDBC or legacy persistence code to entity-based mappings
- Resolving N+1 queries, excessive loading and transaction faults
- Designing inheritance, composite keys and entity relationships
- Reviewing mappings, queries and database interaction before release
What strong professionals deliver
A capable JPA specialist models aggregates carefully and keeps entity behavior separate from accidental database details. They select fetch plans deliberately, understand persistence contexts and explain when a native query is safer than a complex JPQL expression. Their deliverables can include mapping designs, query reviews, migration plans, tests and clear technical documentation.
Working with a Frankfurt specialist
Companies in Frankfurt can involve JPA professionals in banking, insurance, logistics, commerce and other data-intensive sectors. On-site collaboration may help with architecture workshops or access-sensitive systems, while remote work suits focused implementation and review. Clear requirements around Java versions, the persistence provider, database platform, delivery language and team rituals make collaboration more effective.
Frequently asked questions
Curious about Jakarta Persistence (JPA)? Here are the answers that come up again and again.
Jakarta Persistence (JPA) maps Java objects to relational database tables and manages their lifecycle within transactions. Companies use it for domain models, queries, relationships and durable data in enterprise applications and services.
JPA provides object-relational mapping, entity lifecycle management and portable query concepts above JDBC. Direct SQL or JDBC can offer tighter control and predictable database-specific behavior, so a strong specialist chooses between them rather than forcing every query through an abstraction.
Jakarta Persistence (JPA) is a specification, while Hibernate is a widely used implementation of that specification. Hibernate adds provider-specific features, but projects should keep core mappings portable when migration flexibility matters.
JPA work benefits from strong Java, SQL and relational database knowledge. Familiarity with Spring or Jakarta EE, transactions, REST services, Flyway or Liquibase, testing and observability is also valuable when persistence problems cross application boundaries.
The right level depends on the risk and scope of the work. A straightforward mapping task may need focused persistence knowledge, while a legacy migration or performance investigation calls for a JPA specialist who can inspect SQL, transaction boundaries, database design and application behavior together.
Jakarta Persistence (JPA) projects are often suitable for remote collaboration because code reviews, profiling data and database design sessions can happen online. Frankfurt-based teams should define access controls, meeting expectations, documentation standards and whether German or English is required for daily work.
Ask how the specialist would investigate an N+1 query, choose fetch strategies and handle transaction boundaries. A strong JPA professional explains trade-offs, shows evidence from generated SQL or profiling, and leaves behind tested mappings and understandable documentation.
Jakarta Persistence (JPA) allows teams to select an implementation such as EclipseLink, Hibernate or OpenJPA. The choice can depend on existing application standards, Jakarta EE integration, provider features, support requirements and how much implementation-specific behavior the project needs.
The average hourly rate of freelancers in Frankfurt, Germany who have used Jakarta Persistence (JPA) in their recent projects is 91 €, which corresponds to a daily rate of about 725 € 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 
Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
Berlin 
Hamburg 
Munich 
Cologne 
Dusseldorf Countries:
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