EasyMock Experts in Germany
for reliable Java tests, matched in minutes with vetted and available freelancersHire experts who create maintainable Java unit tests with mock objects, strict interaction checks and JUnit integrations, while FRATCH connects you quickly with precise, vetted and available freelance specialists.
Meet FRATCH Experts in Germany, who have recently used EasyMock
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
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.
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.
Achille C.
Last position:
Backend/Frontend Developer at ITZ-Bund
Development of a microservice application for calculating postings on accounts
Development of backend components with Java or JEE, Quarkus, Kafka, Rest API
Development of the test component with mocking frameworks (Mockito)
Development of integration test components
Creation of OpenAPI specification format
Configuration of CI/CD pipeline
Development of frontend components with React
Design, further development and optimization of system structures
Code review
Java Corretto 21, JEE, Quarkus, Golang
Reactive programming with Spring WebFlux, Project Reactor
Git, Azure DevOps for CI/CD pipeline, YAML, Json Swagger UI, Postman, Rest OpenAPI, Kafka Streams, Kafka Connect, Log4J
Microservices, Jira, Confluence, MySQL, Docker, Kubernetes (deployment via Helm charts)
Spring Security, OAuth 2, JWT, Sonarqube
IntelliJ, Maven, logging framework Splunk, Agile method Scrum, Nexus, Vaadin V24, build tool Vite
React, React.JS, Node.js, Jess/JavaScript, Tailwind CSS, Agile method Scrum, accessibility BITV, Playwright
Ioan D.
Last position:
Senior Software Developer at ING
- Tribe Home, Product Area 4 - Customer in Life, Squad Cybertron.
- Analysis, design, development, and testing of new requirements for Optimmo, construction financing software.
- Analysis, design, development, and testing of the JEE application MWS kredit-baufi.
- Analysis, design, development, and testing of the Wicket Optimmo application.
- Analysis, design, development, and testing of kredit-baufi batch programs.
- Migration of kredit-baufi batches to RHEL9.
- CiL SCS Consumer Pacts with Finagle.
- CiL ScS Touch Point Architecture Integration.
- Team size: 10.
- Tools / Frameworks: OpenJDK Java 17, Kotlin 1.6.0, Azure, Jenkins, Stash, JEE, Gitlab, JIRA, Confluence, git, Spring 6.0, Sping Cloud, Spring Data, Hibernate, JPA, JMS, Kafka, Oracle, PL/SQL, Red Hat Enterprise Linux (RHEL), Maven, REST, JBoss, Intellij IDEA, Wicket 9 and 10, Istio.
Michael K.
Last position:
Atruvia AG
- Further development of framework components and services in the Enterprise Banking Control Platform (EGP Framework), a set of cross-cutting libraries and services for all bounded context scopes of the platform.
- Migration from Java 17 to Java 21 and from Spring Boot 3.2 to 3.4 in about 80 library and service repositories (updating Maven POMs, Dockerfiles, Jenkins pipelines, source code migration, test updates).
- Writing unit and integration tests with JUnit and JGiven.
- Performing and analyzing performance measurements with Dynatrace.
- Enhancing multi-stage CI/CD pipelines (unit tests, security analyses, Docker builds, Harbor deployments, ...).
- Tech stack used: Java (90%), Python (10%), Spring Boot, JPA/Hibernate, JGiven, OpenAPI, Camunda 7, Podman, OpenShift/Kubernetes, Oracle DB, SonarQube, Dynatrace, Jenkins, Harbor, Bitbucket, Jira, Confluence.
Vladimir M.
Last position:
Developer at Financial services provider
- Support and further development of a framework for developing applications in a banking association: DynS/OSPE
- Migration of the framework to Java 11 and Java 17
- Java8, Java11 and Java17, Spring, Spring-Batch, Spring WebServices, Spring-Security, Spring-Data, JPA, Hibernate, OpenSource libraries etc.
- XML, JAXB, JSON, REST and SOAP services, DB2, Oracle, WebSphere or Liberty AS, FreeMaker, Junit, mock libraries, JaCoCo, Maven, IntelliJ, Eclipse, GitHub, SVN, Jira
Rolf M.
Last position:
Lead Developer and Reviewer of Specialized Applications for the 2021 Census Project at Federal Statistical Office
- Kubernetes, AWS Cloud, Docker, RESTful Services, ActiveMQ, Oracle Advanced Queuing, JBoss EAP, Spring Batch, Git, Keycloak, Kafka, Maven
- Set up CI/CD pipelines with Jenkins
- Developed automated integration tests
- Performed DevOps tasks
- Regularly performed static code analyses during development on all releases of the Census specialized applications using SonarQube
- Set up an R server for household generation
- Set up a Kafka server for the CVTS application
- Set up a Keycloak instance
- Set up a Jira instance to carry out the Jira migration
- Set up an IRI Workbench instance and Cosort for test data creation
- Set up test systems for Java web applications with JBoss8, JDK17 and Oracle and MySQL databases
- Set up the associated Oracle databases, including functionally relevant data
- Identified weaknesses in the technical communication between the specialized applications
- Built extensive business and technical knowledge of all Census specialized applications
- Supported and advised the departments on Census business processes in pre-production and production
- Performed load and performance tests with JMeter and Bash scripting
Walid E.
Last position:
Solution Architect & DevOps Consultant at Extra Something – IT Consulting
- Technical leadership and architecture for enterprise clients (including LR Health & Beauty, Deutsche Bahn, Trusted Shops)
- Cloud migration, microservices architectures, CI/CD optimization
Reinhard D.
Last position:
Continuing Education Data Analytics, Artificial Intelligence, Deep Learning, Machine Learning at Continuing Education
- Continuing education in Data Analytics, Artificial Intelligence, Deep Learning and Machine Learning
- Operating system: Windows
- Development environments: JetBrains PyCharm, Jupyter Notebook, Spyder
- Programming languages: Python 3.10
- Other technologies: Anaconda, Keras 2.10, NumPy, OpenCV, Pandas, Scikit-learn, Seaborn, TensorFlow 2.10, PyTorch
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.
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
Duc Tu L.
Last position:
Freelance Software Developer at Source Group International - on behalf of Christoph Kroschke Holding GmbH & Co. KG
- Technologies used: Ubuntu Linux, IntelliJ, Gitlab CI/CD, Java 17, Kotlin, TypeScript, Angular, Maven, Spring Boot, PostgreSQL, Hibernate, JUnit, Mockito, Docker, AWS, Keycloak, Kafka
- Designed and developed a new in-house project in a microservice landscape
- Backend with Java/Spring Boot and frontend with TypeScript/Angular
- Deployed the microservices on AWS Fargate
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))
Igor K.
Last position:
Freelance Software Developer
Discover over 15,000 top freelancers
Statistics of experts using EasyMock
Aggregated from the professional profiles of matched freelancers.
Experience
24 years
Position duration
1.9 years
Positions per freelancer
18
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Product Development, Business Intelligence
Bachelor's degree or higher
100%
Master's degree or higher
83%
Doctorate
25%
Certifications per freelancer
2
Most common languages
German, English, Persian
Speak two or more languages
93%
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 Germany 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 Germany using EasyMock
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.
EasyMock 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 (93%)
- Banking and Finance (73%)
- Automotive (67%)
- Insurance (53%)
- Transportation (53%)
- Government and Administration (53%)
- Retail (47%)
- Education (40%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What EasyMock does
EasyMock is a Java library for creating mock objects in unit tests. It lets a test define expected method calls, arguments, return values and invocation order without starting real databases, messaging systems or external services. This isolates a class and makes its behavior easier to verify.
Core testing model
A typical EasyMock test moves through record, replay and verify phases. During recording, the test describes the interactions a mock should receive; replay runs the production code, and verification checks that the contract was respected. Strict, default and nice mock modes support different levels of interaction control.
Java ecosystem
EasyMock fits into established Java testing stacks rather than replacing them. Specialists commonly combine it with JUnit 4 or JUnit 5, Maven or Gradle, Java interfaces, dependency injection and CI pipelines. They may also work with PowerMock, Mockito or hand-written test doubles when legacy code or a different mocking style requires another approach.
- Define expectations for collaborators
- Return controlled values and exceptions
- Verify call order and argument use
- Integrate tests into build and CI workflows
When companies use it
Companies bring in freelance expertise when a Java codebase has fragile tests, heavy external dependencies or difficult-to-isolate business logic. EasyMock is useful during legacy modernization, regression-test expansion, service refactoring and release preparation. Teams in Germany may choose remote collaboration for focused test work, with on-site sessions when domain knowledge and close coordination matter.
Signs of strong expertise
A strong professional uses mocks to clarify behavior, not to reproduce every implementation detail. They keep expectations readable, avoid overspecified tests and know when a real integration test or simpler stub is safer. Good specialists also inspect test failure messages, improve fixture design and explain why a mock belongs in a test.
- Separate unit, integration and contract-test concerns
- Keep tests deterministic and fast
- Refactor production code for testability
- Review brittle expectations and hidden coupling
Bringing EasyMock into delivery
Freelance support can cover test design, mock migration, flaky-test diagnosis, JUnit integration and documentation. The right scope depends on the codebase, test architecture and release risk rather than on the library alone. Agree on Java versions, build tools, repository access, review practices and working language before starting; German or English collaboration can both work when expectations are explicit.
Frequently asked questions
Everything clients usually want to know about EasyMock, in one place.
EasyMock is used to create mock objects for Java unit tests. It allows a test to define expected calls and controlled responses from collaborators, so a class can be tested without relying on databases, queues or remote services.
EasyMock uses an explicit record, replay and verify workflow, with strong control over expected interactions. Mockito generally offers a more gradual, verification-focused style, so the better choice depends on existing test conventions, readability needs and the level of interaction control required.
A strong EasyMock specialist should also understand JUnit, Java interfaces, dependency injection and Maven or Gradle builds. Experience with CI pipelines, integration testing and Mockito helps when a codebase uses more than one test-double approach.
The required depth depends on the codebase. EasyMock work in a small, well-structured module may need focused testing expertise, while a legacy Java system often requires broader skills in refactoring, dependency analysis and regression-test design.
EasyMock projects are often suitable for remote collaboration because tests, build files and review discussions can be shared online. On-site work in Germany can still help when the specialist must understand a complex domain, coordinate with several teams or support a sensitive modernization effort.
Review whether EasyMock tests express business behavior clearly and fail for useful reasons. Look for focused tests, limited duplication, stable expectations, meaningful argument checks and a sensible balance between mocks, stubs and integration tests.
EasyMock may be a poor fit when tests become dominated by interaction scripts or when a real integration test would provide stronger confidence. It can also add friction in code with unstable collaboration boundaries, where simpler stubs or a different mocking style are easier to maintain.
An EasyMock freelancer can deliver unit-test suites, mock-based regression coverage, JUnit integration, failing-test diagnosis and migration guidance. They may also document test conventions, reduce brittle expectations and improve production code so dependencies are easier to replace in tests.
The average hourly rate of freelancers in Germany who have used EasyMock in their recent projects is 96 €, which corresponds to a daily rate of about 767 € based on an 8-hour working day.
Of the freelancers in Germany who have used EasyMock in their recent projects, 100% hold at least a Bachelor's degree, 83% hold at least a Master's degree, and 25% hold a doctorate.
On average, freelancers in Germany who have used EasyMock in their recent projects have 24 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Germany who have used EasyMock in their recent projects are German (100%), English (87%), and Persian (13%).
The most common industries among freelancers in Germany who have used EasyMock in their recent projects are Information Technology (93%), Banking and Finance (73%), and Automotive (67%).
The most common business areas among freelancers in Germany who have used EasyMock in their recent projects are Information Technology (100%), Product Development (93%), and Quality Assurance (80%).
Main locations of FRATCH Experts, who have recently used EasyMock
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 Request a free demo
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Philipp Thomaschewski
FRATCH CEO
