Mockito Experts in Munich
in minutes from over 15,000 CVs with the power of AI.Hire experts who write clean Mockito test suites, mock Spring and Java dependencies, and stabilize unit and integration tests for complex services. In Munich, they also support teams that need clear test design, fast onboarding, and smooth collaboration with in-house specialists. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Mockito
Fred Hauschel
Last position:
Software Architect and Developer at Personal project
A recurring problem in my own AI-supported projects: requirements analysis, use cases, and architecture decisions can be created quickly with AI support, but they remain hard to trace 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 as a continuously linked knowledge graph, traceable from the requirement to the architecture decision – queryable for both people and AI agents alike. Technically based on RDF/OWL and its own MCP server.
Result: MCP daemon running, Docker image automatically published on GHCR, nine hexagonal modules, eleven ADRs (including an open-core licensing model). Requirements engineering and ubiquitous language hexagon active. Publicly available since 07/2026 as a Community Edition under Apache-2.0 (github.com/kogn-io/arknet), together with the Claude Code plugin and the 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
Marcus Biel
Last position:
Java Cloud Expert at Unknown
- Modernized and modularized a legacy monolith to enable independent team workflows
- Migrated from Java 8 to Java 21 and from Spring Boot 2 to Spring Boot 3.3
- Simplified Maven project structure, reducing build time from 15 minutes to 50 seconds
- Converting architecture to a hexagonal DDD architecture with end-to-end integration tests using RestAssured and JUnit 5
- Tools and technologies: Java 8-22, Spring Boot, Mockito, AssertJ, RestAssured, Hibernate, OracleDB, Flyway, REST, JSON, Docker, Kubernetes, AWS, Bitbucket, GitHub, SonarQube, IntelliJ IDEA Ultimate
Alexander Schwartz
Last position:
Founder and Full-Stack Developer at TrumpPostAlert.com
- Feasibility study for quick implementation of requirements with AI-based development (vibe coding)
- Development of a single-page web app in Angular 20
- Development of a backend server application in Kotlin
- Integration with Google Cloud Platform (Firebase): authentication, Firestore NoSQL database, storage, Cloud Functions, hosting and Cloud Run
- Integration with a NEON PostgreSQL database
- Automated AI-based analysis of Donald Trump's posts on Truth Social and analysis of relevance for stock markets and geopolitical topics
- CI/CD via GitHub Actions using Docker and Google Cloud Run
- Technical environment: Angular 20 (Angular Material, RxJS), Kotlin 2.2.20, TypeScript 5.9.3, Spring Boot 3.5.6, Google Cloud Platform (Firebase, Cloud Run, Gemini, Vertex AI), ChatGPT Codex, Git, GitHub, SourceTree, IntelliJ WebStorm, IntelliJ IDEA
Celso Kurrle
Last position:
SAP Commerce Cloud FullStack Developer at Spar
- Implementation of a GitLab CI/CD pipeline based on SAP Commerce Cloud 2211
- Development of a new B2C shop with Vue, Node and TypeScript to ensure scalability, extensibility and performance optimization
- Integration of Microsoft Azure Event Grid with SAP Hybris
- Implementation of BDD with Cucumber using Gherkin syntax to promote collaboration between development and business teams
- Support and customization of a Spartacus shop
- Technologies/Languages: Java, REST, OData, Behavior Driven Development (BDD), Cucumber, Node, Vue, TypeScript, Spartacus, GitLab CI/CD, Gradle, Maven, Ant, SonarQube
Vitor Rodrigues
Last position:
Test Coordinator Automation at Pro4all
- Designed and built from scratch the automation framework using Playwright, Typescript, JavaScript, Gherkin, Cucumber, BDD, Maven, IntelliJ IDEA
- Defined, developed and maintained test plans, test scripts, reports and other QA documentation in Confluence
- Created and maintained test data with SQL Server Management Studio, Toad and Faker.js
- Performed web services and API testing using Swagger Open API, SoapUI, JSON, HTML and XML
- Executed functional, smoke, regression, black box, GUI, cross-browser, UAT and E2E testing using CrossBrowserTesting and Safari Web Inspector
- Integrated and maintained automated scripts within sprints following Kanban, CI/CD, GitHub, Docker, Azure Pipelines, Agile, Scrum, Kafka and Kibana
- Raised and managed defects in Azure DevOps
- Conducted mobile testing with Robot Framework and Appium
Abhijit Ingle
Last position:
Lead Backend Developer and Architect at Gloresoft GmbH
I have worked across multiple international client projects, holding senior roles including Software Architect, Senior Software Developer, Technical Lead, and Lead Backend & DevOps Engineer. My experience spans complex enterprise environments in banking, financial services, telecommunications, engineering, and automotive domains, supporting organisations such as UniCredit Bank, Telefónica O2, and BMW.
At UniCredit Bank, within the Securities Domain Transformation program, I led the modernisation of legacy monolithic systems into cloud-native Spring Boot microservices and an Angular frontend deployed on Google Cloud Platform. Beyond implementation, I was responsible for defining the target architecture, producing system architecture diagrams and sequence diagrams, and preparing API contract documentation for clients. I designed RESTful APIs and integrated Apigee for secure and reusable cross-project service consumption of APIs. I architected Kubernetes-based deployments using Helm. CI/CD pipelines were built with Jenkins, automating code analysis using Sonar, as well as testing and deployment stages. Defining clean coding principles for the project, conducting regular code reviews, and mentoring junior developers were also among my tasks at UniCredit.
At Telefónica O2, I led the transformation of a legacy call centre desktop application into a cloud-native microservices and micro-frontend solution. I actively contributed to the platform architecture, creating system architecture diagrams, component diagrams, architecture documentation, and ADRs for future references. I improved the performance and scalability of the services. I optimised AWS infrastructure costs, particularly by minimising the use of DynamoDB and reusing test environments effectively. Observability was implemented using Prometheus, Grafana, CloudWatch, and Splunk dashboards. CI/CD pipelines were delivered using GitLab, Docker, Kubernetes, and AWS. Conducted techinical sessions for teams.
Syamala Himabindu
Last position:
Fullstack Developer at BLG Logistics Group
As part of developing this project, various apps were developed for an IBM portal environment based on portlets and Spring Boot services, as well as the setup of a BI platform based on QlikView
Full-stack development of applications, technical analysis, refinement of requirements with the business department, coordination with the customer, DevOps
Team size: 8 people
Technology: Java 11.0, Maven, Git, Spring, Hibernate, JUNIT, Mockito, React, Jira, SQL, Spring Boot, CD/CI Jenkins, Kanban, Rest Api, Oracle
Environment: Eclipse, IBM Rational Application Developer
Christian Stellwag
Last position:
Senior Java Developer at Freelance
- Numerous projects as a Senior Java Developer or Team Lead in the technical domain, banking sector, public sector, etc. Please ask for a detailed project list. My contact: office(at)stellwag.it
Bela Bocsak
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.
Jamal Baydoun
Last position:
Freelance Software Architect & Developer at IBM Deutschland GmbH / BWI GmbH
- Architecture, design and further development of a hybrid solution consisting of a Java backend with REST API and C# / WPF frontend
- Development of secure, distributed functions for classified message processing, categorization and encryption
- Integration of backend services with document management systems (DMS) for structured file storage
- Planning, setup and continuous optimization of Azure DevOps pipelines for automated deployment and quality assurance of distributed applications in a security-critical environment
- Technical coordination with Bundeswehr project managers and third-party providers of relevant software and interfaces, and documentation of the developed solutions
Janusz Mazurek
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))
Discover over 15,000 top freelancers
Statistics of experts using Mockito
Aggregated from the professional profiles of matched freelancers.
Experience
26 years (Germany: 19 years)
Position duration
2.3 years (Germany: 1.8 years)
Positions per freelancer
16 (Germany: 13)
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Government and Administration
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
71% (Germany: 60%)
Doctorate
14% (Germany: 11%)
Certifications per freelancer
1 (Germany: 3)
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 96%)
Based on our profile pool as of 30 Aug 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 Mockito
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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What Mockito does
Mockito is a Java testing library for creating mocks, stubs, and spies in unit tests. It helps specialists isolate code, verify interactions, and keep tests focused on behavior instead of setup noise. Teams use it to test service layers, API clients, and business logic with clear expectations.
Where it fits
- Unit tests for Java and Kotlin code
- Mocking repositories, services, and external APIs
- Verifying calls, arguments, and edge cases
- Testing Spring-based applications without real dependencies
It is often chosen for projects built with JUnit and Spring Boot, where fast feedback matters more than full end-to-end coverage.
Skills around it
Strong Mockito professionals understand test structure, dependency injection, and the difference between mocks, spies, and real objects. They know when to use argument matchers, captors, and strict stubbing, and when a simpler test is better. In Munich, they often work with teams that want readable test code and low-flake builds.
When companies need help
Companies bring in freelance expertise when tests are hard to maintain, when legacy code has poor coverage, or when new services need a solid test strategy from the start. They also seek support during framework upgrades, refactoring work, or when a build has become slow and brittle. A good specialist can turn unclear tests into a stable suite.
Ecosystem and tools
Mockito is usually used with JUnit 5, AssertJ, Hamcrest, Spring Boot, and build tools such as Maven or Gradle. It also appears in projects that use test doubles for REST clients, messaging components, and persistence layers. Good professionals understand how these tools fit together in a Java test stack.
What strong specialists deliver
Strong Mockito experts write tests that are easy to read, easy to debug, and hard to break. They keep mocking focused, avoid overuse, and design tests that protect behavior without locking code into implementation details. The result is a test suite that helps teams move faster with confidence.
Frequently asked questions
Curious about Mockito? Here are the answers that come up again and again.
Mockito is used to create test doubles in Java unit tests so code can be checked without calling real services, databases, or APIs. Teams use it to verify behavior, isolate failures, and keep tests focused on one unit at a time. It is a common choice for service classes, client wrappers, and Spring-based code.
Mockito is not a replacement for JUnit; it works with JUnit to support assertions and test execution. Compared with EasyMock, it is usually seen as more flexible and easier to read for many Java teams. Companies often choose it when they want clean interaction testing without heavy setup.
A strong Mockito specialist should also know JUnit 5, Java, and basic test design. In many projects, Spring Boot, AssertJ, and Gradle or Maven are part of the same stack. Knowledge of dependency injection and clean code patterns also matters.
A Mockito project usually needs outside help when tests are hard to trust, legacy code is tightly coupled, or refactoring has made the suite noisy. It also helps when a team is moving to a new test style and wants clearer patterns. An expert can fix the structure without turning every test into a mock-heavy script.
Yes. Mockito work is usually easy to do remotely because it centers on code review, test design, and pair sessions rather than hardware or lab access. In Munich, freelancers often join on-site workshops for legacy systems and then continue delivery remotely with the same team.
Look for tests that read like behavior, not implementation steps. A strong Mockito professional avoids over-mocking, uses clear names, and knows when a real object is better than a mock. Good signs are stable tests, simple setup, and a suite that still makes sense months later.
Mockito is mainly for unit tests, but it can also help in integration-style tests when a project needs to replace external dependencies at the edges. It is less about proving the whole system and more about controlling specific collaborators. For broad end-to-end coverage, teams usually combine it with other testing tools.
Ask how they decide between a mock, a spy, and a real object, and how they keep tests maintainable. With Mockito, the best answer is usually about test clarity, not just syntax. It also helps to ask how they handle legacy code, argument matching, and brittle tests in your current codebase.
The average hourly rate of freelancers in Munich, Germany who have used Mockito in their recent projects is 88 €, which corresponds to a daily rate of about 703 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Mockito in their recent projects, 100% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Munich, Germany who have used Mockito in their recent projects have 26 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Munich, Germany who have used Mockito in their recent projects are German (91%), English (91%), and Spanish (27%).
The most common industries among freelancers in Munich, Germany who have used Mockito in their recent projects are Information Technology (100%), Banking and Finance (82%), and Government and Administration (64%).
The most common business areas among freelancers in Munich, Germany who have used Mockito in their recent projects are Information Technology (100%), Product Development (91%), and Project Management (55%).
Main locations of FRATCH Experts, who have recently used Mockito
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 
Cologne 
Frankfurt 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!
Philipp Thomaschewski
FRATCH CEO
