Spring Boot Experts in Frankfurt

The Base Services of DB InfraGO form a central data hub between the company’s IT systems. Common Data Services are developed that distribute data from source systems to a variety of downstream systems (via JMS) and make them available (via REST API). The existing service landscape based on TIBCO is being migrated to DB InfraGO’s cloud-native platform.

• Architecture design and implementation for performance-optimized bulk data processing of several million datasets at specific times during the day
• Technical specification and documentation of business requirements
• Integration of various subsystems (including SAP and Salesforce) through the reimplementation of more than 40 microservices based on Spring Boot
• Migration of TIBCO Based microservices from the Enterprise Integration Platform to the Cloud Native Platform using Spring-Boot
• Establishment of a deployment pipeline using GitLab CI/CD, Artifactory, and automated deployment to a Kubernetes environment with the help of ArgoCD
• Definition and implementation of automated unit, integration, and regression tests

Team Size: 9

Technologies/Tools: Java, Spring Boot, ActiveMQ(JMS), JUnit, Tibco Business Works, Gitlab (CI/CD), Kubernetes (Amazon AWS), ArgoCD, postgreSQL, Oracle, Postman, Hoppscotch, openAPI, Sonarqube

• Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
• GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
• AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner

• Development and optimization of the RTL+ frontend application for SmartTV and set-top box platforms with React and Next.js.
• Key role in the technical coordination of developers within the team and in coordinating implementation.
• Central interface to adjacent teams to simplify development processes and improve cross-team alignment.
• Improved frontend performance, stability, and rendering behavior on low-powered devices in a restricted runtime environment.
• Implemented a frontend testing strategy with Jest, React Testing Library, and Playwright.
• Implemented accessibility improvements according to WCAG 2.2 and WAI-ARIA.
• Integrated Didomi Consent Management as a contribution to increasing ad monetization on streaming platforms.
• Used AI-supported engineering workflows with Cursor for structured implementation, refactoring, and faster problem solving.

Technologies used: React, Next.js, TypeScript, JavaScript, GraphQL, Apollo Gateway, Zustand, Tailwind CSS, Styled Components, React Testing Library, Playwright, Jest, HTML5, CSS3, AWS Lambda, EC2, CloudFront, S3, GitLab CI/CD, NX, Cursor

• Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
• Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
• Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
• Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
• Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
• Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
• Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka

• Conducting and evaluating web analyses
• Creating and editing tags and scripts in the area of tag management as well as banners and other client-side web elements in the area of consent management
• Technologies used in development: Tealium, JavaScript, IntelliJ, Git, Android Studio, Selenium, Appium, Adobe Analytics, Power Automate, Power App

• Platform established and running stably; deliberately reducing my involvement to refocus on an engineering mandate in the financial sector.
• Built an own SaaS learning platform from the ground up and scaled it to over 20,000 users (over 6,000 courses sold, B2C and B2B); end-to-end ownership from development through infrastructure to operations.
• Built a lab environment that provisions an isolated Linux container per user (Docker, Traefik, Go), including automatic provisioning and a dedicated subdomain per user.
• Integrated LLM features into the product and accelerated development end-to-end with AI-assisted workflows (Claude Code, Codex); CI/CD with automated tests.

Project: SCS (Settlement / Clearing Services)

Settlement platform serving multiple trading and clearing venues — counterparty risk safeguarding, settlement volume reduction, central risk management, and post-trade anonymity.

Technologies: Java 17, Spring Boot 3, Microservices, Spring Data JPA, SonarQube, Fortify (SCST), Mockito, Jenkins, OpenShift, Maven, Podman, GitHub, JIRA, Liquibase, Swagger, AMQP, Apache Camel, Terraform, PostgreSQL, Instana, Graylog.

• Identified and remediated CVEs in third-party libraries using SCA tooling, strengthening the security posture of production components.
• Maintained 90% code coverage with SonarQube, improving code quality and reducing production defects.
• Enabled mTLS for database authentication and message broker connections, enforcing encrypted, certificate-validated communication.
• Designed and deployed microservices with asynchronous, REST-based communication between components.
• Optimized a high-volume REST API (~200K requests) by reducing response time from 3s to 2s (33% improvement), boosting throughput and reliability under production load.
• Automated build and continuous integration pipelines using Maven and Jenkins.
• Orchestrated containerized workloads on Podman/OpenShift and governed schema evolution with Liquibase, ensuring reliable, repeatable deployments across all environments.
• Optimized Java code and implemented EHCache-based caching, improving application performance.
• Streamlined release management by governing application images, JAR versions, and dependencies through DBAG Artifactory, ensuring version consistency and audit traceability across environments

• Porsche ID is a unified digital identity platform providing secure authentication and seamless access across Porsche’s online services, mobile apps, and connected vehicle features
• Designed and implemented new authentication and authorization functionalities for both users and systems
• Ensured high availability, security, and performance to deliver a flawless digital experience for Porsche customers
• Technologies: Auth0, Angular, Tailwind, AWS, Terraform, Github
• Methodologies: Scrum and SAFe

• Introduction of methods for developing and automated deployment of cloud-native software and machine learning applications in OpenShift clusters
• Development of various programs in Python
• Technologies: Kubernetes, OpenShift, Kustomize, ArgoCD, Tekton, Docker, PodMan, Airflow, IntelliJ, PyCharm, Git, Bitbucket, Jira, Confluence, Python

• Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
• Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
• Storage of the silver layer on Hadoop and the gold layer in Oracle.
• Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
• Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
• Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
• Versioning changes in GitHub and deployment via the CI/CD portal.
• Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
• Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
• Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
• Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
• Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.

• Database design with Oracle DB, JPA and Flyway considering high performance requirements
• Analysis of multiple architecture drafts and identification of technical risks
• Design and implementation of various interfaces and integrations, especially REST APIs and Kafka topics
• Setup of Elasticsearch for monitoring and analyzing log data
• Establishment of an iterative work approach in the project team facing complex business requirements

AI-powered platform for automated UX validation and designer support

• Designed and led technical implementation of an enterprise-wide AI solution for automated UX review that improved design quality and significantly reduced manual review processes in teams
• Developed an automated UX validation tool as a Figma plugin and web application that generates test cases based on internal guidelines and reliably checks current designs for consistency and standard compliance
• Implemented an interactive designer chat based on RAG that answers questions about the current design and the company's UX guidelines, and designed the deployment architecture using containerized services
• Python, Azure OpenAI, PostgreSQL, REST API, Docker, OpenShift, Helm, CI/CD, Figma MCP, LLM, RAG, Prompt Engineering, GenAI, XAI, AI Architecture, AI Strategy

• Testing the SekIDP and related components
• Test design, execution and automation, microservices, GitHub Enterprise, Eclipse, Katalon Test Platform, API Testing, Confluence 8, JIRA/Xray, Draw.io, Swagger/OpenAPI, Postman, Docker, Kubernetes, Podman, PuTTY, E-Health, Telematik, Gematik standards, EPA, E-Rezept, sektoraler IDP, encryption, XaDES, PaDES, DICOM, HL7, FHIR, IHE, ICD, SSO, SAML/Shibboleth, OAuth, smartcards, JWT, two factor authentication Android and iOS, Wireshark, BrowserStack, Cypress, gRPC, REST, SOAP, WS-Security, Linux Shell, PowerShell, SSH/SSL, Java, Kotlin, Cordova, Gradle, Groovy, Python, TypeScript

• Involved in the full development lifecycle, including design, coding, testing, and deployment of Java-based applications.
• Built and maintained high-performance RESTful APIs and microservices, ensuring scalability and reliable data exchange.
• Practiced code reviews, used version control systems (e.g., Git), and collaborated closely with cross-functional teams to deliver robust software solutions.
• Implemented, managed, and optimized complex business logic and decision-making processes using the Drools Rules Engine, leveraging DRL (Drools Rule Language) for dynamic configuration.
• Developed software solutions for a major service provider in the healthcare insurance sector, specifically focusing on claims processing and reconciliation logic to ensure cost-effective reimbursement for health funds.