
Jakarta Persistence (JPA) Experts
to build reliable data layers, matched with vetted freelancers in minutesHire experts who design entity models, optimize database access and integrate Jakarta Persistence (JPA) with Spring, Hibernate and transactional Java applications. FRATCH uses fast, precise AI matching to connect you with vetted, available freelancers.
Meet FRATCH Experts who have recently used Jakarta Persistence (JPA)
Kathrin S.
Last position:
Requirements Engineer at Governikus GmbH & Co. KG
- Impact: Structured requirements analysis and quality assurance as a foundation for the further development of a software solution.
- Analysis, documentation, and coordination of requirements. Conducting stakeholder analyses, interviews, and workshops to gather and validate requirements. Conducting requirements reviews and working closely with business departments and development teams.
Techniques & Tools: Requirements Engineering, Stakeholder Management, Workshop Facilitation, System Context Modeling, Requirements Reviews, Quality Scenarios, Miro, Jira, Confluence
Khalid E.
Last position:
Lead Architect & Developer at kem-consulting
Development of an agent-based governance platform for the automated assurance of EU AI Act compliance and ODA-compliant orchestration of AI services in complex enterprise environments.
Design and implementation of an agent-based "Mission Control" framework (Aletheia Conductor) for autonomous state monitoring and process control.
Development of "Compliance-as-Code" (CaC) solutions based on OPA/Rego for system-wide enforcement of regulatory guardrails.
Integration of TM Forum ODA standards (TMF630, TMF622, TMF642) to ensure interoperability and standardization.
Building a highly available event-driven architecture using Redpanda and CloudEvents v1.0 for near-real-time event processing.
Implementation of an audit-proof "Evidence Chain" through cryptographic linking of trace logs in preparation for automated audits.
Tech Stack: Java 21 (Quarkus Native), TypeScript (Next.js), Redpanda (Kafka API), CloudEvents v1.0, OPA (Open Policy Agent) & Rego, TimescaleDB, ZincSearch, Redis, TM Forum ODA, Git, GitHub, Clean Code Development, Like-C4.
Harold T.
Last position:
CPU Watcher — Cloud-Native Monitoring Application at SEUYTEL
- Planned and developed a CPU monitoring application for monitoring system performance and resource utilization.
- Designed and implemented a Spring Boot backend providing a REST API for processing and exposing monitoring data.
- Developed the React frontend for presenting monitoring information in a clear and user-friendly interface.
- Integrated PostgreSQL for persistent storage and management of application data.
- Containerized the application and its services using Docker Compose.
- Automated infrastructure provisioning and deployment using Terraform on AWS.
- Structured the application as a modern, maintainable system using REST-based communication between frontend and backend.
- Designed and developed a secure, scalable CPU monitoring architecture (cpu-watcher) with a dedicated collector application that streams monitoring data to the backend, reducing direct exposure of system resources.
- Designed a secure cloud infrastructure with the database isolated within a private network and OIDC-based authentication.
- Implemented Infrastructure as Code with Terraform and integrated version-controlled CI/CD pipelines to automate testing, infrastructure changes, and application deployments.
- Designed and implemented the frontend delivery architecture using AWS CloudFront.
Stack: Spring Boot · React · PostgreSQL · REST API · Docker Compose · Terraform · AWS
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
Marcus B.
Last position:
Java and Quarkus Expert at Large German energy service provider
- Modernization of a large-scale Java enterprise application*
The project is modernizing a complex enterprise application that has grown over many years. The existing Spring-based legacy system runs on Java 8, OSGi, and Eclipse RCP and is being gradually migrated to a modern, maintainable architecture with Java 25 and Quarkus.
Marcus works on analysis, architecture, refactoring, and implementation. One focus is on untangling historically grown structures and dependencies and on building a clean, sustainable Java and Quarkus technology stack.
Tools & technologies: Java 8, Java 25, Quarkus, Hibernate ORM with Panache, EclipseLink, OSGi, Eclipse RCP, Maven, JUnit, Mockito, REST, JSON, Git, Eclipse IDE, IntelliJ IDEA Ultimate, Jira, Confluence
Hooman B.
Last position:
Fullstack Developer at Möbel Roller GmbH
- Further development of the existing e-commerce platform based on SAP Commerce (Hybris) to meet the growing demands of digital commerce.
- Ensuring the scalability and performance of the backend, so the platform remained stable and efficient even under heavy user load.
- Development and integration of new OCC REST APIs and services for modular extensions and flexible adjustments, to implement new features quickly.
- Optimization of data flows and interfaces, which significantly improved platform efficiency and system performance.
- Ensuring a maintainable and scalable code base by using Clean Code principles, proven design patterns, and a future-proof architecture.
- Reduction of errors through extensive testing with JUnit, Mockito, and load tests with Gatling, supported by the introduction of automated test processes.
- Improved system performance through targeted refactoring measures and efficient database queries, especially to handle peak loads.
- Use of modern cloud and monitoring tools such as Kubernetes, Google Cloud Platform (GCP), and Grafana to ensure a stable and monitored infrastructure.
- Clear improvement in efficiency, scalability, and reliability of the platform, which now meets the demands of a dynamic and growing e-commerce market.
Marijn S.
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
Niko S.
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.
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
Priyanka S.
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
Osman T.
Last position:
Senior Architect, DevOps Engineer at genPsoft GmbH
IT consulting, analysis, architecture design, new and further development, code review, test automation, continuous integration, continuous delivery in backend and frontend areas for Automotive Project Instavalo.
Frontend:
- Implementation of UI components according to specifications, especially style guides and responsive design eith React and Typescript
- Component testing
- Code documentation
- CI/CD with Gitlab Pipeline
Backend / IoT:
- Analysis and architectural design with AWS Greengrass IoT on Edge Devices
- Setting up Microservices containers with Docker Compose on Edge device with AWS Greengrass and AWS IoT IAM, Token Exchange Service, Ansible
- CI/CD with Gitlab Pipeline, Terraform, AWS ECR
- Logging with Fluentbit Lua Language for AWS Cloudwatch
- Python Lambda for AWS Greengrass Recipe deployment on Edge Devices
- Implementation of test-driven development with JUnit, Mockito, and code Coverage
- Jacoco
- Definition of REST interfaces with OpenAPI / Swagger
- Development and enhancement of software based on Java Quarkus, Typescript NestJs NodeJs and Python
- Authentication and authorization in Aws IAM
- Development of REST and gRPC interfaces for the frontend and backend
- Implementation of Maven dependencies with DevSecOps OWASP
- Spring AI, Jetbrains AI Assistant, Junie, Github Copilot, Claude Code, Agents, Skills, Command, Hooks, Subagents
Sercan T.
Last position:
Co-Founder & Lead Software Architect at Pflege-Pfad
- Focus: system architecture, cloud-native platforms, microservices, API design
- Product: Pflege-Pfad is a digital matchmaking platform that connects relatives of people in need of care directly with verified care services and caregivers - without an agency and without ongoing fees.
- Business analysis & process design:
- Analysis of the German care market and identification of the key pain points of both target groups.
- Modeling of the core business processes: registration, verification, care request, application, placement, and rating.
- Definition of the business model as a freemium/premium model with optional contact unlocking.
- Creation of user stories and requirements documentation for relatives, care services, and administrators.
- Design of trust and quality assurance mechanisms with document upload, admin review process, and rating system.
- Coordination with stakeholders and validation of product decisions with potential users.
- Technical implementation:
- Design and implementation of the entire platform architecture as a solo developer.
- Design and implementation of a REST API with Spring Boot and Kotlin, including JWT-based authentication.
- Development of the frontend as a single-page application with Angular 17.
- Implementation of the AWS infrastructure with EC2, RDS PostgreSQL, S3, CloudFront, and IAM.
- Document upload with AWS S3 via presigned URLs for verification of care services.
- Email notifications via Resend API.
- AI-supported care service search via OpenAI API.
- Implementation of complete user flows such as registration, login, password reset, and placement process.
- Building an admin panel for user and care service management as well as analytics.
- CI/CD with GitHub Actions and containerized deployments with Docker.
- End-to-end tests with Playwright.
Technologies: Kotlin, Spring Boot 3, Spring Security, JWT, JPA/Hibernate, PostgreSQL, Angular 17, TypeScript, RxJS, AWS (EC2, ECS, S3, CloudFront CDN, RDS PostgreSQL, IAM), nginx, GitHub Actions, Playwright, Maven, Git, OpenAI API, Resend API, Docker, Scrum, i18n (DE/EN/TR), Kiro, feature-flag architecture.
Thorsten M.
Last position:
Odoo Implementer at N.N.
As project manager for the Odoo implementation at a small company, I was responsible for designing, implementing, and training a fully integrated CRM and accounting system. Through structured requirements analysis, precise data migration, and targeted change management, I was able to complete the rollout in just eight weeks. The project led to a significant reduction in manual tasks, faster business processes, and increased real-time transparency.
Main Responsibilities
Requirements analysis and process mapping Configuration of Odoo modules: CRM, Sales, and Accounting Data migration (Excel/CSV → Odoo) and quality control Creation of workflows, automated email rules, and dashboards Conducting training sessions and providing support after go-live Project coordination (budget, schedule, stakeholder communication)
Key Achievements
Full implementation of the Odoo suite within the set timeframe (8 weeks) 30% reduction in accounting time and 25% acceleration of the lead-to-sale flow 100% customer satisfaction after go-live, based on survey results Successful migration of 100% of existing master data without data loss Establishment of a sustainable support infrastructure (3-month post go-live support)
Impact
Improved decision-making through real-time dashboards and automated reports Increased efficiency and cost savings (≈ €8,000/month) Scalability for future growth (additional modules can be integrated seamlessly) Strengthened sales and finance departments through seamless process integration
This summary highlights how I created concrete and measurable value for the company through structured project work, technical expertise, and targeted training.
Tamás E.
Last position:
Senior Software Developer / Tech Lead at NDA (defense / OSINT)
- Designing the audit logging framework
- Implementing APIs for developers to integrate in their codebase
- Implementing ingestion pipeline, database query layer and UI for browsing the audit events
- Improving stability and reliability of the backend system
Stefan A.
Last position:
Sole Architect and Developer at Bauernhof-Eis Stangl GbR
Design and implementation of a compact ERP, CRM, accounting, and production-planning platform for a German food manufacturer. The system replaces Rechnung11, self-built Excel sheets, and manual processes for fewer than 10 internal users.
- Designed and implemented the full platform architecture as sole architect and developer.
- Built modules for customer management, B2B order handling, invoicing, production planning, and accounting support.
- Implemented DATEV export, ZUGFeRD/XRechnung e-invoicing, FinTS bank statement synchronization, and GoBD audit trail concepts.
- Used AI-supported workflows for prototyping, test support, and implementation acceleration while retaining full architecture, review, testing strategy, and technical ownership.
Technology: Java 23, Spring Boot 3, Spring Data JPA, Spring Security, Vue 3, TypeScript, PostgreSQL, Flyway, REST, OpenAPI, JWT, TOTP, RBAC, DATEV, FinTS, ZUGFeRD, XRechnung, GoBD, JUnit, Mockito, Testcontainers, Playwright, Docker, GitLab 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
2 years

Positions per freelancer
13

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
96%
Master's degree or higher
55%
Doctorate
10%

Certifications per freelancer
3

Most common languages
German, English, French

Speak two or more languages
96%
Based on our profile pool as of 26 Sep 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 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 26 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 (99%)
- Banking and Finance (61%)
- Retail (42%)
- Automotive (41%)
- Government and Administration (39%)
- Insurance (36%)
- Transportation (35%)
- Manufacturing (34%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Persistence fundamentals
Jakarta Persistence (JPA) is the standard Jakarta EE specification for mapping Java objects to relational database tables. It defines entities, relationships, persistence contexts, repositories and transaction behavior without forcing an application to depend on one database vendor. The former Java Persistence API name still appears in project documentation and search queries.
Data modeling work
JPA specialists turn business concepts into maintainable entity models and database interactions. They handle identifiers, inheritance, embedded values, cascading, fetching strategies and optimistic locking. Their work supports transactional services, business applications, customer portals and internal systems that need consistent access to relational data.
- Map entities and relationships to an existing schema
- Design repository and query patterns
- Resolve lazy-loading and transaction-boundary issues
- Improve persistence tests and migration readiness
Ecosystem and tooling
Strong expertise usually includes Hibernate ORM, the most common JPA implementation, as well as EclipseLink or another provider where project constraints require it. Professionals work with Jakarta EE runtimes, Spring Data JPA, CDI, REST services and relational databases such as PostgreSQL, MySQL and Oracle. They also understand Maven or Gradle, Flyway or Liquibase, SQL logging and database migration workflows.
When specialists help
Companies often bring in freelance JPA expertise when a legacy Java application needs modernization, a data model is becoming difficult to change or production queries are slowing down. A specialist can also establish persistence conventions for a new service, review a Hibernate configuration or support a migration from javax.persistence to jakarta.persistence. Remote collaboration works well when schema decisions, pull requests and test environments are documented clearly.
- Review an existing persistence layer
- Prepare a Jakarta EE or Spring migration
- Investigate inefficient queries and excessive loading
- Create repository and integration-test standards
What quality looks like
A capable professional treats JPA as a persistence boundary rather than a substitute for database knowledge. They can explain the SQL generated by mappings, choose fetch plans deliberately and recognize when a native query is safer than a complex object query. They also protect transaction boundaries, validate cascade behavior and test concurrency, constraints and rollback paths.
Project fit and delivery
The right specialist starts by clarifying the database engine, schema ownership, application framework, deployment model and expected transaction behavior. Deliverables may include entity classes, repositories, JPQL or Criteria queries, provider configuration, migration guidance, performance findings and tests. For ongoing work, clear documentation and consistent naming make it easier for Java teams to review and extend the persistence layer.
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 transactions. It provides standard annotations, entity management and query APIs for applications that need structured access to persistent data.
JPA reduces repetitive mapping code and lets teams work with domain objects, relationships and portable query abstractions. Direct SQL still offers tighter control for reporting, complex database features or performance-sensitive operations, so strong specialists know when to combine both approaches.
Jakarta Persistence (JPA) is a specification, while Hibernate ORM is an implementation of that specification. Hibernate supplies provider-specific features and behavior, but applications can use the standard persistence APIs to reduce dependence on one implementation.
JPA work benefits from solid Java, SQL and relational database knowledge. Useful adjacent skills include Hibernate, Spring Data JPA, Jakarta EE, REST services, transaction management, database migrations with Flyway or Liquibase, and automated integration testing.
For a contained mapping or repository task, a specialist mainly needs to understand the schema, transaction boundaries and existing conventions. Larger modernization or performance projects require someone who can analyze generated SQL, provider behavior, migrations, concurrency and the wider application architecture.
Jakarta Persistence (JPA) projects are well suited to remote collaboration when the schema, local setup, migration process and acceptance criteria are documented. Teams should also agree on review practices and use shared test environments to reproduce transaction and query issues.
Ask how the professional would investigate slow queries, unexpected extra selects, detached entities or incorrect cascade behavior. A strong JPA specialist should discuss execution plans, fetch strategies, transaction scope, database constraints and tests rather than relying only on annotations.
Jakarta Persistence uses the jakarta.persistence package namespace, replacing the older javax.persistence namespace in newer Jakarta EE applications. A migration can involve imports, dependencies, runtime compatibility and provider versions, so the specialist should review the full application stack instead of changing package names blindly.
The average hourly rate of freelancers who have used Jakarta Persistence (JPA) in their recent projects is 93 €, which corresponds to a daily rate of about 743 € based on an 8-hour working day.
Of the freelancers who have used Jakarta Persistence (JPA) in their recent projects, 96% hold at least a Bachelor's degree, 55% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers who have used Jakarta Persistence (JPA) in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers who have used Jakarta Persistence (JPA) in their recent projects are German (97%), English (97%), and French (14%).
The most common industries among freelancers who have used Jakarta Persistence (JPA) in their recent projects are Information Technology (99%), Banking and Finance (61%), and Retail (42%).
The most common business areas among freelancers who have used Jakarta Persistence (JPA) in their recent projects are Information Technology (99%), Product Development (96%), and Quality Assurance (64%).
Main locations of FRATCH Experts, who have recently used Jakarta Persistence (JPA)
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:
Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!

Berlin
Hamburg
Munich
Cologne
Frankfurt
Dusseldorf
Vienna