JSON Schema Experts in Germany

Consumer Cards Solution Architect

• Provided architectural leadership in Consumer Cards Domain establishing best practices and improving architectural transparency and maintainability by designing a structured documentation framework to enable reverse engineering of legacy card systems.
• Standardized architectural artefacts including BIAN Business Capabilities, UML diagrams in draw.io format (Use Case, Component, Sequence), naming conventions, document repository, design templates and blueprints, microservices.
• Produced high-level and low-level designs aligned with enterprise architecture governance processes and artefact standards.
• Provided architectural support to the Strategic Card Simplification Programme, focusing on card product migrations and application decommissioning across all countries. Agile environments (Scrum/SAFe).
• Analysed and designed AI use cases in the architecture domain.

Project: Payment Card Industry Data Security Standards (PCI DSS) Strategic Programme

• Analysed and documented existing data flows across card products and geographic regions to assess PCI DSS compliance.
• Identified areas involving sensitive data at rest and data in motion requiring encryption or masking, ensuring adherence to PCI DSS requirements.
• Collaborated with security, infrastructure, and application teams to align encryption strategies with regulatory and organizational policies.
• Provided strategic advisory services on data strategy, data governance, data management, data quality, data architecture, data mesh, MEGA HOPEX, DAMA-DMBOK, event-driven architecture, end-to-end data flows and card product harmonization models.
• Ensured solution design alignment with regulatory compliance (BCBS 239, DORA, GDPR) and internal policies.

Project: Denmark ATM Outsourcing Project

Objective: Outsource ATM operations and maintenance to a third-party provider while expanding the Denmark ATM fleet, with Nordea retaining ownership of ATMs and cash for the existing and extended infrastructure.

• Led a cross-functional delivery team (project management, business analysis, and architecture) and documented the as-is ATM ecosystem architecture, including end-to-end data flows, integrations, and internal/external application interfaces.
• Designed end-to-end processes for authorization, reconciliation, and settlement, aligning operating model, controls, and compliance requirements across Nordea and the outsourced service provider.
• Produced high-level and low-level solution designs using standardized UML artefacts (Use Case, Component, and Sequence diagrams) to support vendor onboarding, integration planning, and implementation.
• Ensured architectural alignment and decision-making across enterprise stakeholders and third-party providers, managing dependencies and interfaces in the context of the outsourcing initiative.

• Created internal web application to improve the salary process using a microservice interfacing with MSSQL
• Developed interactive web UI using Microsoft Blazor
• Integrated Azure AD for user authentication
• Designed and implemented roles and permissions in the database
• Developed progress page guiding users through each process step
• Processed bonus calculations by importing Excel files
• Configured email notifications using MSSQL Send Mail
• Tools and technologies: C#, ASP.NET 6, MS-SQL, REST API, Visual Studio 2022, TFS, microservices, Kanban Board, Azure DevOps

• Clarification of project goals, scope, and functional target vision for building the AI-based knowledge base.
• Deriving the initial architecture and implementation strategy for the Zasterbot chatbot, including defining the MVP and expansion phases.
• Developing a functional target vision for building a structured knowledge base and integrating a future chatbot.
• Deriving and prioritizing use cases for information retrieval and provision by the chatbot.
• Modeling data structures and flows for effectively organizing the knowledge base on the Base44 platform.
• Designing and implementing data models for storing and linking relevant information.
• Developing processes for extracting, analyzing, and preparing raw data for the knowledge base.
• Ensuring data consistency and quality as the foundation for the future chatbot.
• Planning the integration of large language models (LLMs) and retrieval-augmented generation (RAG) for precise and context-aware responses.
• Implementing features for analyzing and visualizing data from the knowledge base.
• Using the Base44 platform with JSON-schema-based entities and a flexible permission model.
• Implementing Deno functions for backend logic, event processing, and external API integration.
• Integrating OpenAI services for initial data analysis.

• Implemented accessibility audit recommendations for the ICE onboard portal to improve usability for screen reader and keyboard users
• Migrated end-to-end tests from Cypress to Playwright
• Refactored components to meet accessibility standards
• Introduced Prettier for consistent code formatting

• Overall management of several project streams: mechanical development, IoT integration, software development, plant design, validation
• Management of an international project team made up of mechanical engineers, electronics engineers, software developers, designers, and external suppliers
• Coordination of global stakeholders from Germany, France, India, China, and the USA
• Planning, controlling, and reporting across all project levels: schedule, budget, resources, and deliverables (PMI-oriented)
• Moderation of steering committees, technical workshops, and milestone decisions
• Responsibility for requirements management and prioritization in the overall context (IoT, cloud, mechanical integration, safety standards)
• Quality assurance and test strategy: validation of filtration results, system behavior, plant integration
• Supplier management and procurement involvement for components, logistics, and assembly
• Risk management and escalation handling for technical, regulatory, or cross-country deviations
• Go-to-market preparation: coordination of product documentation, CE certification, training, and handover to service & sales
• Methods: multiproject management according to PMBOK, hybrid model SCRUM + classic milestone planning, stage-gate model
• Tools: MS Project, Excel, Jira, Confluence, Miro, MS Teams, SharePoint, CAD/CAE systems, test and validation software
• Technologies: OPC UA, MQTT, Siemens S7, IO-Link, Modbus, REST APIs, SCADA, monitoring dashboards, sensors & control technology, CE-compliant housing design, ISO standards

• Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
• Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
• Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
• Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
• Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)

• Designed and implemented end-to-end automated workflows for extracting structured data from semi-structured PDF documents including invoices and medical reports
• Leveraged Optical Character Recognition (OCR) technology and large language models to parse documents and generate validated JSON schemas
• Engineered prompt optimization strategies and rule-based classification hierarchies to enhance parsing accuracy across diverse document layouts
• Established quality assurance framework using evaluation metrics to validate output against ground truth datasets with 96% accuracy

• API-first product design (OpenAPI 3, HAL) and development (NodeJS)
• Setting up DevOps pipelines with GitHub Actions in an AWS architecture
• Technologies: OpenAPI 3, REST, HAL, NodeJS, JavaScript, TypeScript, AWS, AWS Lambda, Docker, GitHub Actions

Detecting and classifying vehicles in images and video for traffic monitoring

• A YOLO + Faster R-CNN model built for real-world traffic and autonomous-vehicle scenarios. Awarded Best Paper Award at St Joseph Engineering College, March 2025.

What it does

• The model takes images or video frames and both localizes and classifies vehicles by type, making it usable for downstream applications such as traffic-flow monitoring or perception in autonomous-vehicle systems.

What I did

• Combined YOLO (for fast detection) with Faster R-CNN (for higher-precision classification), rather than relying on a single architecture, trading off speed and accuracy where each mattered most.
• Achieved 90% mean Average Precision (mAP), evaluated using IoU-based metrics rather than just raw accuracy, to properly reflect localization quality.
• Handled the full data processing and evaluation pipeline in Python using TensorFlow and OpenCV.
• The accompanying paper was awarded the Best Paper Award by the Department of CSE at St Joseph Engineering College.

Tech stack: Python, TensorFlow, OpenCV, YOLO, Faster R-CNN

• Dashboard application for visualizing power generation and consumption as well as profitability calculations for a photovoltaic system.
• The software is built in a strictly modular way and can be used in many different settings, including on devices like the Raspberry Pi or NAS systems, and offers connection options for a wide range of PV systems.
• A steadily growing community values the intuitive operation and the high reliability of the tool.
• The source code is open source, and development is funded through a sponsorship model.
• Technologies: Ruby on Rails, InfluxDB, Docker, MQTT

• Architecture and design of the application
• Development of new features
• Integration with AWS backend (GraphQL, REST)
• Deployment on AWS
• Gatsby, React, Redux, Material UI, TailwindCSS, ChartJS, Plotly, GraphQL, GitLab