Visual Studio Code Experts

Reporting and controlling with Power BI for a productive ERP system

• Analysis of ERP data and interfaces for use in Power BI dashboards
• Evaluation and migration of existing reports (e.g. Excel) to Power BI
• Development of an access rights concept for selective data access
• Documentation and training on how to use and adapt the Power BI dashboards

Label: Power BI, Excel, SelectLine ERP, Microsoft SQL, SQL Server Management Studio

Creation of concepts for M365 implementation, especially Tenants, EntraID, EntraConnect and ExchangeOnline, taking BAS standards into account (mandatory baseline security requirements) in the project "Concept M365" with the aim of transferring the concepts to the M365 environments of Bitmarck and then handing them over to the customer.

• Creation of a current-state analysis of the existing M365 environments as well as the on-premises environments and the BAS standards.
• Creation of concepts for the topics Tenants, EntraID, EntraConnect and ExchangeOnline taking the BAS standards into account
• Design and implementation of an automated solution for creating standardized M365 tenants based on Microsoft M365 DSC (Desired State Configuration)
• Transfer of the concepts into the M365 environments
• Creation of detailed technical documentation

• 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

Project goal: Carrying out system tests and validating industrial communication and control systems, including requirements definition and verification.

Responsibilities:

• Test planning, test execution
• Test strategy, test cases, and test specifications
• Requirements analysis
• Ensuring traceability between requirements, test cases, and defects
• Carrying out regression and integration tests
• Defect analysis
• Simulation and validation
• NetSniffer Wireshark
• Supporting test automation (Python, CI/CD)
• Reporting
• Stakeholder coordination and agile collaboration (Scrum / SAFe / Kanban)
• V-Model
• CI/CD automation with Python, Groovy, and frameworks (Selenium, PyTest)

Technologies:: CAN, Modbus, Ethernet, PLC, PROFINET, Codebeamer ALM, Scrum, SAFe, MS Teams, Git, CI/CD with GitLab CI and TeamCity, Windows Batch, FAS, Wireshark, Python, Enterprise Architect (EA), AI tools (e.g. ChatGPT, Microsoft Copilot), VS Code, Tia Portal, SCL, Python (Selenium, PyTest)

• Consulting across two integrated areas: Commercial Strategy (pricing, sales steering, marketing strategy, market expansion, margin management) and Operational Efficiency (process automation, AI integration, workflow design, last-mile automation).
• Development of custom SaaS solutions, explicitly tailored to the specific requirements and processes of each company.
• Delivery of AI training and change management workshops for managing directors and specialist departments, including AI competence training with a certificate of attendance under Art. 4 of the EU AI Act.

• Designed and developed a multi-tenant SaaS platform enabling organizations to build their own knowledge bases and chat with brand-customized AI assistants (white-label approach with dynamic branding per organization).
• Implemented a scalable RAG architecture with a GPT-4o tool-use loop, hybrid semantic search, and strict tenant isolation at database and search index level.
• Built persistent, project-like chat sessions including a streaming API (SSE), multilingual support, and speech input/output (STT/TTS).
• Delivered the cloud infrastructure as Infrastructure-as-Code, fully automated per-customer CI/CD pipelines, and an onboarding process for new tenants.

Technologies used: Python, FastAPI, Pydantic (v2 noted), Next.js, React, TypeScript, Tailwind CSS, OpenAI / LLMs (GPT-4o), Azure AI Search, Cosmos DB, Azure Blob Storage, Azure Cognitive Services Speech, Azure App Service, Azure Container Registry, Retrieval-Augmented Generation (RAG), Server-Sent Events (SSE), Docker, Terraform, GitHub Actions, REST, OpenID Connect (OIDC), Multi-Tenancy

• Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
• Implementation of automated end-to-end cloud processes
• Development of LLM and NLP models
• Creation of interactive reports
• Support for national and international large corporations as well as medium-sized companies in implementing ML projects

• Further development and operation of a central backend service for providing vehicle inventory for international Mercedes-Benz online shops
• Further development of a reservation service for vehicles as part of the checkout process
• Design and implementation of a highly scalable end-to-end test architecture with a focus on maintainability, reusability, and a high number of automated test cases
• Development of a multi-layer test infrastructure with a strict separation of test logic and access layers
• Development of an initialization and caching architecture to significantly speed up local and CI/CD-based test runs
• Development of an AI-supported review architecture for automated evaluation and quality assurance of end-to-end tests
• Development of a dashboard for consolidated display of a vehicle context across multiple backend systems, including AI-generated summaries and compact case analyses
• Integration and further development of connections to various reservation systems via Apache Kafka and REST
• Design of new microservices and support with architecture decisions
• Risk analysis and design of microservice migrations
• Technologies: Java, Spring, Spring Boot, Gradle, Maven, Apache Kafka, REST, OpenAPI, Swagger, Github, Confluence, CI/CD, Microservices, AI, LLMs

• DTO class generator: In-house development of a tool for the automatic generation of classes, functions, and methods for use in .NET Core projects based on SAP Business One Service Layer metadata
• E-invoice import add-on: Development of a SAP Business One add-on / coresuite module for the automated import of ZUGFeRD e-invoices as incoming invoices – with configurable mapping to flexibly control the import logic across four mapping types (DIRECT, SQL, FIXED, EXPR). The add-on is available as a licensed product for SAP Business One customers.

Stack: SAP Business One, SAP Business One Service Layer, coresuite Country Package, C#

Independent product design practice supporting startups and growing companies with enterprise SaaS, workflow architecture, product strategy, and AI-enabled product development.

• Deliver end-to-end product design for digital products, websites, and SaaS platforms, combining product thinking, UX, visual design, and implementation.
• Apply AI throughout the product lifecycle—from research, synthesis, information architecture, and prototyping to development, SEO, and content strategy.
• Design and build production-ready digital products using AI-assisted workflows, enabling significantly faster iteration and delivery.
• Advise founders and businesses on product positioning, UX strategy, and digital transformation.

• Built and fine-tuned CNN and RNN architectures using transfer learning for real-world classification tasks — core deep learning skills applicable to BMW's multimodal LLM and GenAI vehicle function development.
• Implemented Dropout, Batch Normalisation, and Early Stopping across deep learning experiments; evaluated rigorously using precision, recall, F1-score, and confusion matrices for production-grade reliability.
• Developed an AI-powered attendance management system using LBPH facial recognition, deployed via Flask web interface with real-time SMS notifications — demonstrating end-to-end AI product delivery for real users.
• Collaborated across cross-functional teams to deliver scalable, documented ML pipelines designed for reproducibility — matching BMW's interdisciplinary team and research environment.
• Integrated AI tooling directly into the development workflow from design through to testing, maintaining high velocity without compromising correctness.

• Developing the infrastructure and improving existing infrastructure: Jenkins, Gitlab Pipeline, OpenShift, Docker, Helm Chart, Kubernetes, Artifactory, CodePipeline, CodeArtifact, Python
• Documenting solutions in Jira/Confluence
• Supporting other colleagues in different technical areas

• Overall responsibility for the project lifecycle from scope definition to completion
• Close collaboration with platform teams, IT leaders, and external service providers
• Application of SAFe principles and structured sprint work
• Creation of a migration roadmap with clear milestones
• Monitoring of the lifecycle: onboarding, repository migration, replication of permissions, and system tests
• Visualization of the architecture with PlantUML and Gliffy as well as documentation in Confluence
• Regular status reports and running knowledge transfer sessions

• Automotive SPICE®: all assessments fully achieved
• Agile transformation: V-model → SAFe successfully implemented
• Series release: on-time, quality-assured software delivery for key Volkswagen Group models (including ECE homologation)
• Stakeholder management: internal & external
• Process optimization: implemented a continuous improvement process (CIP) with a tracking system