GitLab Experts in Hamburg

• Onboarded and conducted comprehensive documentation and system analysis to assess the existing data infrastructure, facilitating rapid integration and collaboration across functional data teams (modelling, processing, reporting).
• Collaboratively defined the architecture and project structure for a central data pipeline repository, including hierarchical standards, knowledge management strategies, and role-specific responsibilities, enhancing maintainability and onboarding speed.
• Evaluated and validated open-source data routing tools (Airbyte, Apache NiFi, Dragster) for ingest and sync requirements in retail analytics, including local benchmarking and error-state testing.
• Led the design and deployment of Airbyte in Kubernetes, creating customized Helm charts, securing secrets handling, and configuring Ingress with TLS and internal DNS routing, ensuring full API and UI accessibility.
• Troubleshot and resolved Ingress controller issues, iterating through multiple stages of debugging and testing, and documented setup and replication steps for scalable reuse.
• Mapped data models to ARTS standard, supporting schema alignment for ERP and reporting use cases, and coordinated review loops to align future data processing logic.
• Drafted strategic 1-pagers comparing MinIO, Pub/Sub, and routing architectures, providing technical guidance for architectural decisions and investment planning.
• Enabled secure access and authentication mechanisms, including initial evaluation for SAML integration, cluster-level configuration reviews, and service annotation improvements.

• Designed and implemented a Python-based ETL pipeline with the Dagster framework to transform raw energy data from heterogeneous sources using InfluxDB and visualizations in Grafana
• Defined time-based and dependency-based jobs
• Deployed to managed Kubernetes clusters using Helm
• Integrated InfluxDB Cloud
• Prepared data for use in Grafana, including cleaning, normalization, and time-based resampling in Python
• Developed dashboards and visualizations in Grafana
• Developed unit tests with mocking using pytest
• Set up a CI/CD pipeline in GitLab

Technologies: Python, Dagster, InfluxDB, Grafana, pandas, pytest, REST, CI/CD, GitLab, Container, Kubernetes, Helm, Docker, Cloud

• Building an AI & Data Consultancy Practice with the goal of helping European companies adopt Artificial Intelligence and modern data platforms
• End-to-end further development of a production system using modified coding agents (OpenCode). Tech stack: Kubernetes, Argo, Keycloak, Typescript, Grafana, GitOps, DevOps, Playwright
• Internal research project on the use of coding agents in the field of mathematical logic for creating formal models. Use of Cursor IDE and Codex, Codex CLI. Architecture design, quality control and refactoring, as well as writing code and tests. Repository (open source) available pre-launch
• Research on the role of mathematical logic as a formal language that connects IT and AI with business processes
• Project lead for collecting and deploying parking recommendations for rail vehicles with significant savings potential based on real-time data in a mobility and transport company
• Project lead for collecting and distributing process measurement points for real-time control in a mobility and transport company
• Deputy application owner for an app used for communication in the dispatching and provision of rail vehicles

• Remodeling of the system architecture for an Azure-based platform aimed at rapid development of new functionalities
• Modeling of a staging concept for the fulfillment of diverse customer and QA needs
• Creation of requirements for, and oversight of, a proof-of-concept supplier project for a Flutter app with highly advanced BLE functionalities
• Comparison of multiple observability platforms for feasibility and requirements fit within the project environment
• Creation of a mobile app architecture based on domain-driven architecture
• Position of technical advisor and accountable solution architect for two development teams
• Execution of architecture reviews and alignment of changes with architectural expectations
• Skills & Technologies: Microsoft Azure , App Services, NodeJS Mono-repository, microservice architecture, domain driven design, self contained systems, requirements engineering, CI/CD, DevOps, API design, solution architecture

traigo is VTG's digital rail logistics and fleet management platform. It processes large volumes of telemetry, mileage, geofence, sensor and wagon-movement events in near real time and provides operational services for rail logistics customers across Europe.

As part of Team Customer Selfcare, I worked on the design, implementation, optimisation and operation of large-scale backend services and event-driven processing pipelines — covering both feature development and operational ownership of business-critical production systems. I also regularly acted as first responder for production incidents, data inconsistencies and performance investigations across multiple distributed services.

• Design and implementation of event-driven backend services.
• Migration and replacement of legacy processing pipelines.
• Development of replay / rebuild mechanisms for large event datasets.
• High-throughput asynchronous event processing on SNS / SQS.
• Database and query optimisation for PostgreSQL and DynamoDB.
• Design of scalable read / write models and aggregation pipelines.
• Production troubleshooting and operational support.
• Performance tuning and infrastructure scaling.
• Design and stabilisation of integration and system tests.
• Technical concepts, architecture documentation, and cross-team collaboration.
• Support the further development of existing GitLab CI/CD pipelines

Geofence & Wagon Stay Processing

• Algorithm to detect vehicles within geofences (entry, exit, dwell time).
• Event sourcing with guaranteed chronological order within the affected time window.
• Refactored geofence event and wagon-stay processing logic for performance.
• Resolved race conditions and event-ordering problems in distributed services; server-side filtering, aggregation and optimised query pipelines.
• Repair and replay tooling for corrupted or inconsistent movement data.

Fleet Metadata & Mileage

• Modernised the service; migrated storage from DynamoDB to PostgreSQL to improve traceability and accelerate new features.
• Scalable mileage aggregation and replay mechanisms.
• Read / write models and optimised queries for high-volume mileage calculations.

Sensor & Telematics Integration

• Integrated telemetry and sensor processing pipelines.
• Snapshot and state-calculation logic for sensor systems.
• APIs and persistence models for wagon sensor data; data-quality improvements.
• Further development of a service using gRPC for intra-service communication.

Movement Segment Processing & Routing

• Migrated services to new movement-segment event streams.
• Built replay and rebuild tooling for segment correction.
• Optimised throughput and reliability for high-volume event processing.

Condition Monitoring & Wagon Analytics

• APIs and backend services for wagon condition monitoring.
• Brake-wear prediction processing and wagon analytics functionality.
• PostgreSQL views and optimised query models for operational dashboards.

Operational Reliability - First Responder

• Investigated production incidents and distributed-system failures; DLQ analysis, replay and operational recovery.
• Tuned database performance and AWS infrastructure under production load.
• Improved observability, monitoring and operational tooling.
• Supported rollout strategies, monitoring and post-deployment stabilisation.

• Industry: SaaS (Customer Success Management) – B2B

Comprehensive GEO implementation (Generative Engine Optimization) for a B2B CSM SaaS startup with a focus on AI Search Visibility and AI Citations in ChatGPT, Perplexity and Google AI Overviews – including a GEO workshop and a prioritized implementation roadmap.

• GEO Workshop & Roadmap: Conceptualized and delivered a GEO workshop (how LLMs work, AI Search Architecture, citation strategies); translated it into a prioritized implementation roadmap with impact/effort estimates
• Technical GEO Foundation: Robots.txt & llms.txt, Core Web Vitals & page speed, XML sitemaps for AI crawlers
• Schema & Structured Data: Gap analysis, implementation of Product/Service, FAQ, Article, Author and Organization schema, validation of coverage
• Content Architecture & GEO: Flat content architecture, topic clusters (pillar-and-spoke), 200–300 word chunks and answer-first content structure, E-E-A-T rollout through author pages
• Query Fan-Out & Prompt Anticipation: User prompt mapping, query fan-out, content gap analysis based on prompt coverage
• Citation & Backlink Strategy: AI citation analysis (news, Reddit, Wikipedia, listicles) and development of outreach and backlink strategies

Tools & technologies: Otterly.AI, PeecAI, Qforia (iPullRank), Schema Markup Validator, OpenAI Tokenizer, Prompt Coverage Monitor, ChatGPT, Perplexity AI, Semrush, Ahrefs, Framer CMS

I implemented a Zero-Trust architecture for robust, military-grade maritime container mini data centers based on VMware & Tanzu to support containerized GIS workloads for ground forces. The main focus was on securing communications, workload protection, and data access in contested electronic battle environments affected by jamming, interception, signal manipulation, and constantly changing operational conditions. I designed and architected use cases so that every element of workload, identity, and system could continue to operate independently and securely even in degraded or disrupted scenarios. In parallel, I defined the enterprise and solution security architecture with LeanIX, Bizzdesign, and HOPEX as enterprise architecture, repository, and governance platforms to maintain architecture inventory, relationships, traceability, target pictures, and security governance in complex environments. For the architectural designs, I used Sparx Enterprise Architect to describe formal architecture views, interfaces, trust boundaries, and system architecture in both IT and OT environments. IriusRisk was used for threat modeling of the solution to identify architecture-driven risks, derive security requirements, and detect countermeasures and design gaps directly from the solution models. Risk and compliance management was supported with Archer. Architecture decisions, control gaps, and operational risks were translated into controlled governance and auditable compliance measures. For documentation, collaboration, and visual design, I used Confluence to maintain Architecture Decision Records, Security Blueprints, and workflows. I used Lucidchart and draw.io to create design artifacts tailored to stakeholders. I also defined OT security concepts with support from electrical and mechanical engineers in the areas of oil, vehicle onboard systems, rail, power plants, pharma, gas turbines, and nuclear technology. I created the end-to-end OT security strategy, starting with global policy, developed into standards and procedures, and finally aligned with Bell-LaPadula, Purdue Model, SABSA, TOGAF ADM, CENELEC 50701, IEC 62443, and NIST standards. In addition, I worked with engineering team leads to identify critical KBP assets and place them under protective measures that segmented SCADA, PLC, and HMI assets. I drove collaboration between Security, IT, and OT teams to create standardized workflows and use cases for the OT security solution catalog, while integrating Defense-in-Depth and Zero-Trust principles into operational environments. A key part of my work was integrating multidisciplinary engineering, security, and operations stakeholders into a unified security blueprinting strategy and ensuring that architecture, threat modeling, governance, and documentation were technically strong and operationally practical.

• Building new and improving existing features for a housing management platform that helps both landlords and tenants
• Technologies: Node.js, TypeScript, React.js, Next.js, PostgreSQL, Google Cloud, Docker, Kubernetes

• Developing a professional scheduler for organizations with specific detailed requirements
• Evaluating different existing software solutions
• Creating a list of technical requirements
• Implementing these requirements
• Selected technologies: WebDAV, CalDAV, Rust, Baikal, OAuth, Keycloak

• Several projects in a police context
• Model and document police procedures/projects with Archimate (as-is/to-be) in the context of P20 (BKA)
• Create software architectures with microservices
• POC development with Springboot/Docker/Kubernetes
• Project size: 10 people
• Enterprise architecture management with Togaf and Archimate
• Backend software development Springboot
• DevOps with Kubernetes
• Implemented using: Java 17/21, Springboot 3, P20 architecture, Togaf, Archimate

• Owning RAG, LLM-System, ML-ops-Pipelines for various startups in Insurance, Banking, Energy (KRITIS)

• Project lead ‘Cloud Migration’ for moving the on-premise production environment to Scaleway.
• Transformed a Docker-Swarm legacy setup to a modern Kubernetes-based cloud environment.
• Architected a GDPR-compliant cloud landscape and deployment setup – 100% European sovereign cloud.
• Hands-on bootstrapped the cloud environment with Terraform, ArgoCD, and GitLab Pipelines CI/CD.
• Replaced the legacy VPN with modern mTLS PKI and deep AD integration.
• Managed an 11-headed agile team using Kanban, moderating team meetings and plannings.
• Successfully finished the migration, moving infrastructure, services, and data, from planning to execution.

• Performed security assessments and penetration testing on Microsoft AI models for text, image, and video generation.
• Conducted prompt injection attacks through diverse input vectors, including crafted text, steganographic images, and manipulated visual elements (e.g., varying opacity and embedded content).

• 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