Amazon DynamoDB Experts in Hamburg

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.

• Manage and operate the product data import services for the Otto merchant
• Enhance and maintain the backend systems
• Optimize and maintain AWS infrastructure
• Build a new product data import API
• Design and plan stories and features
• Conduct code reviews to ensure code quality and best practices
• Analyze and fix bugs
• Technologies: Java, Spring Boot, Kafka, AWS, Fargate, Terraform, MongoDB, Mongo Atlas, OpenAPI, GitHub, GitHub Actions, GitHub Copilot, Akhq, Debezium, JUnit, Test Containers, Hexagonal Architecture

• Contributed to the development of the Rubix editorial system
• Implemented various microservices based on Java, AWS S3, AWS SQS, AWS SNS, and Spring Boot, deployed to AWS ECS and AWS Fargate
• Designed and developed AWS Lambdas using TypeScript
• Used PostgreSQL in an AWS RDS Aurora cluster and AWS DynamoDB
• Implemented continuous deployment with GitLab pipelines
• Built an Infrastructure as Code environment with AWS CDK
• Set up and maintained a monitoring platform using AWS CloudWatch
• Developed various frontend components with Vue.js
• Designed the microservice architecture applying Domain Driven Design and GraphQL interfaces

• Operation and further development of the inventory system for booksellers (Quimus). It is an in-house development by Libri that is sold to customers as Software as a Service. The software is developed in an agile way by two developer teams (about 5 developers each). The software consists of around 25 Java microservices that mainly communicate via messaging and share a common Angular frontend. The application runs on Kubernetes in AWS.
• Technologies used: Java 17 & 21, Spring Boot 2 & 3, Hibernate, MySQL, Spring Cloud AWS, Lombok, AWS SQS, AWS SNS, AWS RDS, AWS S3, DynamoDB, Kubernetes, Docker, OpenSearch, Hibernate Search, Liquibase, Gradle, Terraform, Helm, GitLab CI, Keycloak OAuth2, TypeScript, Angular
• My focus until December 2023: Connecting additional POS systems to the inventory system. Connecting the data warehouse for report display. Extending existing features (goods receipts, invoicing, item management, ...). Operations and DevOps tasks.
• Focus from January 2024: Extracting the product search from the inventory system into a global service to use in other applications. Integrating the product search into the booksellers' online shops (also run by Libri). Importing and providing digital items in the product search.