MongoDB Experts in Cologne

• Responsible for the architecture and development of an AI-native SaaS platform for industrial product portfolio management.
• Designed the modern data platform architecture on Azure for scalable analytics and enterprise data integration.
• Built enterprise data ingestion and transformation pipelines across complex industrial system landscapes.
• Developed graph-based representations of product structures and dependencies for analytical reasoning.
• Designed and implemented an agentic AI framework for AI-supported decision workflows.
• Built scalable analytical microservices and integrated reporting through modern BI technologies.
• Coordinated backend, AI, and frontend development across the MYNR platform stack.

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

• Evolved the platform from bare-metal infrastructure with a monolithic PHP application to a hybrid Google Cloud architecture with Go microservices on Kubernetes
• Managed and scaled a production infrastructure with 300+ VMs and dozens of clusters, including MySQL, PostgreSQL, MongoDB, RabbitMQ, Redis and Elasticsearch clusters
• Designed architecture, deployment, monitoring, performance analysis, and upgrades for all platform services using Terraform and Ansible
• Migrated observability systems from ELK and Prometheus to Datadog, managed with Terraform
• Introduced Jenkins CI/CD with SonarQube integration and automated tests to speed up feedback cycles
• Containerized the testing environment and implemented GitLab CI pipelines for Docker image builds, static code analysis, and infrastructure tests
• Performed zero-downtime migrations of MySQL and MongoDB clusters to Google Cloud
• Developed reusable Ansible roles for database clusters and automated data obfuscation for staging environments
• Decomposed monolithic databases and migrated to microservice architectures
• Built tools to detect and optimize slow queries in MySQL and MongoDB
• Conducted online schema migrations with pt-online-schema-change without downtime windows
• Developed internal Go applications for batch queries, GitLab-Jira integration, and MongoDB backup recovery
• Technologies: Debian, Ubuntu, Alpine, Go, Bash, Python, PHP, SQL, GitLab CI, Jenkins, Drone CI, MySQL, MongoDB, PostgreSQL, Redis, Elasticsearch, RabbitMQ, Kafka, Docker, Kubernetes, Nomad, Ansible, Terraform, Grafana, ELK, Prometheus, Datadog, Nagios, Zabbix, Nginx, HAProxy, Vault, Helm, SonarQube, Filebeat, Auditbeat, Google Cloud, AWS

• PRISMA project
• Ansible automation
• Windows third level support for Windows NT, Windows 2000, Windows 2013, Windows 2016, Windows 2019

• Two-month modernization of the management UI for AI-powered cameras
• Rewrote a complex React application to Vue 3 with single file components
• Set up the core architecture of the Vue application and configured Vite, Pinia, Router, I18n, ESLint, and Prettier
• Custom integration of Leaflet to display detection zones on images
• Assisted with backend extension and authentication adjustments

• Implementation of custom reporting solutions for financial KPIs aligned with specific business requirements

• Development of a machine learning application that achieved a 250% performance improvement

• Data Architect "Production-Oriented Quality Assurance" (03/2024–09/2024):

• Design and implementation of an analytics platform to detect quality deviations in manufacturing

• Build of a scalable data lakehouse architecture on Databricks in combination with SAP ERP data via SAP Datasphere

• Close collaboration with the SAP team to harmonize bill of materials and order data

• Visualization of KPIs to support shopfloor management

• Lead Data Engineer "Sales Performance Monitoring" (08/2023–12/2023):

• Design and implementation of a Databricks-based platform for analyzing sales figures and promotion effects

• Integration of SAP SD data via SAP BW/4HANA

• Use of Azure DevOps to orchestrate ETL jobs and deploy workflows

• Technical Project Lead "Cloud Migration & Data Strategy" (02/2023–05/2023):

• Migration of a heterogeneous data warehouse stack to a modern cloud architecture on Azure with Databricks as the central processing platform

• Development of a governance-compliant data architecture to integrate SAP financial data and non-SAP sources

Technologies: Databricks, Delta Lake, Python, SAP Datasphere, Azure DevOps, PowerBI, SQL

• Build a sophisticated AI copilot to augment the students’ learning experience and provide AI-derived insights to professors.
• Build a multi-chain LLM system adapting to user needs at its own accord with a Weaviate vector DB based RAG system and evaluated it with Ragas.
• Build responsive react frontend, and backend systems handling auth, data management and auxiliary services as a RESTful API.
• Deployed and managed the app to the cloud in a production environment including the CICD via multi-stage deployment.

• Hybrid role as the first software engineer in the company to bootstrap the organization, laying out technical foundation and advising management on organizational aspects.
• Set up the SaaS platform architecture, selected languages and tools, and designed processes to deliver customer value quickly and reliably.
• Designed and implemented build and continuous deployment pipeline with multi-tenant approach enabling extreme scaling of the SaaS platform.
• Established initial ITSM and support processes, provided monitoring and alarming, and participated in the on-call team.
• Proposed new approaches to scale the platform and improve backend interfaces to mitigate bugs and communication overhead.
• Mentored new employees and served as a trustful team member and lateral leader.
• Conducted interviews for technical roles.
• Used technologies: Typescript, Node.js, Bash, Google Cloud Platform (App Engine, Cloud Run, Cloud Functions, Google Endpoints, Firebase), GitHub Actions, Docker, Terraform, MongoDB, Firebase, REST APIs, GraphQL.

• Develop powerful add-ons for customer service systems with innovative Zendesk apps designed to drive business growth, improve efficiency, and enhance customer satisfaction
• Implement full Zendesk solutions and provide hands-on support to bring customer service vision to life
• Combine customer service and technology expertise to address the complexities of delivering top-notch customer service
• Execute Zendesk implementations in 20+ countries and develop AI apps that automate replies
• Maintain a proven track record of success in advancing customer service capabilities

• Acted as the primary bridge between Legal, Engineering, and Business units to ensure zero compliance violations while maintaining product velocity.

• Led the development of a GDPR-compliant AI aggregator platform, managing a roadmap that balances legal constraints with aggressive feature delivery.

• Scaled the engineering team from 4 to 9 developers, establishing hiring protocols and technical onboarding processes to support rapid product iteration.

• Boosted the development process by introducing structured sprint cycles and backlog refinement, resulting in a 20% reduction in feature delivery time.

• Architected and prototyped agentic AI workflows with n8n and RAG pipelines on Langchain.

• Setting up and enhancing an international subscription management system

• Migrating and decommissioning a Hybris-SAP system and integrating Zuora

• Implementing numerous interfaces to various systems (external and internal)

• Setting up and improving monitoring with Grafana, Prometheus, and Databricks

• Introducing logging with Loki

• Implementing business requirements using jQuery, Thymeleaf, Spring Boot, Java, Go, and Python

• Adjusting and extending the GitLab CI pipelines

• Setting up and extending infrastructure as code with Terraform and ArgoCD on AWS

• Setting up and running E2E and performance tests

• Expanding the Databricks business intelligence solution to provide various KPIs

• Responsibilities: Architecture, DevOps, development, unit tests, coaching employees and apprentices, E2E, smoke, and integration tests, agile methods consulting (Kanban, Scrum)

• Technologies and methods: Java, Go, Kotlin, Node.js, Spring Boot, SOAP/REST, Quarkus, Thymeleaf, Vaadin, Slack, Jira, Confluence, IntelliJ, GitLab, SQS, Kafka, AWS, Kubernetes, Terraform, Maven, Gradle, GitLab CI, Databricks

• Development of an app
• Technologies: React Native, Expo, SupaBase, TypeScript, GitHub, Trello

• Development of monitoring and control systems for public transport
• Development of a platform for real-time monitoring of passenger information and ticketing systems and an application for remote control and status monitoring of access systems
• Development of dynamic forms, complex tables, real-time dashboards (SignalR), and reusable components in the frontend (using Storybook)
• Implementation of REST interfaces in the backend
• Deployment to Microsoft Azure Cloud
• Technologies used: Angular 20, Angular Material 3, Dev Extreme, Storybook, C#/.NET 10