Software Engineer / Architect

Working with the largest privately-operated television station in Germany. My role includes an initial architecture and implementation review for those media streaming systems, which deal with incoming raw content for their broadcasts. Based on that I upgraded and adapted these systems to current coding standards and containerized these services to have them deployable in an existing Kubernetes cloud-native environment:

• Implemented media streaming service, which maxes out available bandwidth for live events

• containerized current systems to run within ArgoCD

• Load tests and performance improvements to manage peak loads

Technical Scope: Spring Boot, Spring Security, Java, Argo CD, Kubernetes, Helm Charts, Docker, GitLab CI/CD, Gatling

The company specializes in NLP research & development and needed to scale their on-premise systems horizontally within the cloud. I was contributing to the design and implementation of new reactive services to parallelize the workload for their non-classified input data. Those data passed through a pipeline of processing steps to be prepared for subsequent classification, based on specialized customer use cases.

• Created Spring Boot services, which integrated event-based via Webflux 

• Contributed to the CD Pipeline by creating Docker images and configuration in Argo CD

• Addressed performance issues by load testing with Gatling and analyzing JVM events

Technical Scope: Kotlin, Java, Coroutines, Reactive Streams, AWS, EKS, Kubernetes, Docker

Backend development of real-time tracking services within the innovation unit of this large logistics provider. The aim is to create services to provide guidance during delivery to consignees. These systems are part of a reactive microservices architecture, to deliver navigation directions localized for several countries. Services are running entirely within AWS, utilizing Kotlin coroutines for asynchronous messaging between the services.

• Push real-time status updates to subscribed handscanner devices of drivers, to immediately redirect them to changed delivery locations;

• Implement a subscription service to notify consignees by SMS when their parcel will delivered within the next minutes;

• Provide parcel updates from an operational data store with async coroutines into SQS queues for further processing following a reactive programming paradigm.

Greenfield IoT project to create a microservice architecture for processing high-resolution sensor data, contributing to automotive production. Incoming data streams are analyzed to determine  whether new products are compliant with regulations and internal standards. The system is operational within ECS, containing both microservices implementations with Spring Boot, as well as serverless components based on AWS Lambda.

• I was involved in this project from a very early stage until after its successful release to production;

• Utilized my knowhow to design and implement highly scalable microservices, with added input from  the automotive engineers;

• Implemented normalization and filtering of sensor data streams for further analysis, provided services to manage configuration of test setups.