RxJava Experts in Germany

Consulting, designing, and implementing the software testing lifecycle for multiple Android apps and backends Introducing test automation with Appium, SpringBootTest, RestAssured Setting up and managing emulators Developing an E2E library, an integration library, a Testcontainers library, and other libraries Developing, implementing, and advising on CI strategies Building the test environment with Testcontainers and virtualization Developing and implementing test cases for integration tests and end-to-end tests Establishing a maintainable test architecture with low entry barriers to simplify the creation of automated tests Some tools and technologies used: JUnit, RestAssured, Testcontainers, Kubedock, Appium, Android emulator, Jira Xray, Mockito, WireMock, Spring Framework, Kotlin

• Prequalified 200 demands within five weeks on the multi-cloud-commerce platform bechtle-clouds.com with three external consultants
• Served a dual role as project manager and requirements engineer for various enhancements
• Domain topics: reimplementation of Entra ID Sync, improvement of support processes, optimizations in the product catalog
• Demand and project management in ServiceNow
• Refinement of epics and stories with internal teams and external service providers
• Management of the external international service provider

• Further development of the Android app "StarMoney"
• Major XML to Compose redesigns
• Introduction of new technologies and architecture
• Implementation of instant bank transfer
• Development following the agile Scrum process

• Intensive language course with a focus on professional language content.

• Optimized the Amp healthcare app alongside a senior developer, specifically enhancing data caching mechanisms which led to a 25% improvement in load times.
• Applied MVI architecture, resulting in a 30% decrease in bugs and streamlining testing processes.
• Implemented CI/CD with Bitrise, reducing deployment sizes from 120MB to 104MB.
• Led the migration of 40% of the Java codebase to Kotlin.
• Achieved 85% unit test coverage.

• Technology update
• Microsoft Azure certification

• Led the development of a doctor scheduling Android app, integrating Jetpack Compose and Kotlin Multiplatform, achieving a 30% performance improvement.
• Implemented complex UI components, ensuring 99.8% crash-free user sessions.
• Seamlessly integrated Compose UI with existing View-based components.
• Optimized API calls, reducing load times by 20%.
• Tech Stack: Kotlin, Jetpack Compose, KMM, MVVM, Koin, Firebase, Stripe API, Crashlytics

• Visualization, search, and maintenance of various types of master data, providing them via a REST API, and implementing a variety of import and export formats.

• Implementation, architecture, project management.

• Technologies and tools: Angular (Signals, Signal Store, swagger-codegen, standalone components), Java, PostgreSQL, ActiveMQ, JavaScript, Spring Boot (Spring Core, Spring MVC, Spring Data/JPA via Hibernate, Spring Security, Spring Modulith), JUnit, Flyway, QueryDSL, GraphQL, REST API, Node, npm, Maven, SonarQube, GitLab CI/CD pipelines, Docker, Nexus, OpenAPI + Swagger UI, Keycloak, OAuth2, OpenID Connect, IntelliJ IDEA, Jira, Confluence.

• Heycar is a leading automotive platform redefining the used car market through intelligent data pipelines, multi-tenant services, and dealer-focused tooling. I led initiatives across backend architecture, data ingestion, and identity management to enhance scalability, reliability, and developer productivity.
• Ingestion Platform: Designed a unified ingestion platform with YAML-based configuration, enabling new dealer data pipelines to be onboarded without code changes, cutting setup time from ~2 months to 2-3 days and improving scalability by 40%.
• Keycloak Leadership: Acted as the company's Keycloak expert, scaling it for multi-tenant identity management and extending functionality with custom plugins and delegated admin APIs.
• Back-Office Tooling: Developed a back-office application integrated with Salesforce, enabling dealers to manage inventory, convert leads, and handle support requests in real time.
• Multi-Tenant Migration: Collaborated across backend teams to migrate Heycar's core services into a unified multi-tenant cluster, ensuring high availability.
• Frontend CI Optimization: Optimized monorepo delivery by implementing CircleCI dynamic config with NX, deploying only affected UI projects and drastically cutting build times.
• Observability & Mentorship: Enhanced monitoring and release reliability while mentoring backend engineers and improving code review standards.

• Built features using Jetpack Compose
• Improved location-based features with in-memory caching
• Developed Merchant-to-Merchant chat functionality from scratch
• Integrated FCM with deep links to enable contextual push notifications
• Performance tuning for Google Maps view using clustering for better performance in dense areas

• Further development of the classifieds app
• Android
• Kotlin
• Coroutines
• Jetpack Compose

• 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))

• Implementing tasks for the Privacy and Trust and Safety team
• Technologies: Kotlin Coroutines, Jetpack Compose, RxJava, Kotlin Room, Dagger, Epoxy, Google Pay