• Manage hybrid Infrastructure in a cross-functional team.
• Manage Kubernetes clusters, on-prem and AKS
• Develop microservices in Java and SpringBoot
• Develop serverless functions in Python
• Containerization of services with Docker
• Follow and establish cloud security best practices, including multiple security layers (e.g. VPC networking, Virtual Machines, Container Cluster ?, and container image security)
• Performance analysis with Splunk APM
• Automate infrastructure provisioning with Bash, Terraform, Packer and Ansible
• Automate build and deployment pipelines
• Integrate Microservices with Keycloak
• Manage distributed Logging (EFK Stack) and monitoring / alerting (Prometheus, Grafana, Alertmanager)
• Continuous Monitoring to ensure performance and reliability of the system
• Build, manage and monitor ETL pipelines with Kafka

• Provisioning kafka clusters with strimzi on Kubernetes.
• Development of kafka stream solutions and connectors to databases
• Development of microservices with Java/Kotlin/Python, SpringBoot (focus on processing of Kafka messages)
• Development of an ML automation solution / pipeline, with Python, Jupyterhub, MLFlow, etc., with a focus on following security best practices in areas like authentication/authorization, encryption and vulnerability scanning
• Administration of Cloud infrastructure ? Hybrid solution, AWS and on-prem Services ? the goal was to integrate data from legacy on-premise services through Kafka / Streams, to a BI solution running in AWS

• Migration of messaging infrastructure from IBM MQ to AWS SQS/SNS
• Dockerization of applications
• Hardening of container images
• Continuous improvement of CI/CD pipelines, with the focus on comprehensive testing and security scanning
• Kubernetes admininstation
• Design and development of a microservice architecture including lambda functions (Java and Python), including some involvement in the development of the AngularJS frontend (frontend architecture, best-practices, code reviews)
• Working on secure coding best practices
• Administration of the entire AWS infrastructure
• Regular refactoring of existing code base, mostly in a pair programming setup
• Configuration of monitoring dashboards and alerts and continuous monitoring of the microservices architecture with the focus on reliability and performance

• Management of Azure Accounts
• Migration of Azure resources from manually provisioned to IaC with Terraform
• Kubernetes (AKS) establishment as standard platform for various services
• Introduction of an application performance monitoring solution to improve system runtime visibility with DataDog
• Regular presentations and training of the dev team to teach and distribute knowledge about the newly acquired Application Performance Monitoring capabilities
• Development of ElasticSearch visualisations to improve operations visibility
• Evaluation and implementation of workflow systems and automation of workflows with Prefect2 and N8N
• CD pipeline development with GitlabCI

• Automated provisoning of diverse AWS infrastrucuture
• Kubernetes Administration
• Implementation of a high availability solution for the GLS hand scanner application
• Setup of HashiCorp Vault
• Improvements of the visibility landscape, including logging (ELK stack), monitoring (Prometheus/Grafana), and APM
• Continuous improvement of stability and performance of applications and troubleshooting of production incidents.
• Development of Deployment Pipelines,
• Development of microservices ans serverless function (Java and Python)

• Development of a Data Pipeliine with Apache Kafka (Streams, Connectors), Kotlin and Scala, in order to consolidate data from disparate data sources
• Evaluation/prototypes development of a new target technology stack, Java/SpringBoot vs. Kotlin/Quarkus
• Migration of existing Scala services to Java and SpringBoot
• Development of GraphQL interfaces
• Administration of Apache Kafka clusters
• Development and operations of AWS infrastructure
• Development of CI/CD pipelines
• IaaS with Python (Pulumi)

• Complete redesign of existing infrastructure to a new target architecture based on Kubernetes (previously services were deployed to plain EC2 instances.
• Redesign of the whole CD pipeline
• Setup of Kubernetes clusters in AWS and integration with AWS services (ELB, Route53, IAM, etc.)
• Provisioning of AWS accounts in a multi-account architecture (Landing Zone)
• Administration of Confluent Kafka and RabbitMQ
• Design and development of microservices (Java/SpringBoot and Python)
• Containerization of microservices
• Setup of a cluster monitoring solution, based on Prometheus/Grafana
• Support of the operations team to establish effective metrics and measurements in order to guarantee early visibility into possible performance degradation and other SRE related issues
• Establishment of application performance monitoring based on DataDog to further increase visibility into the system.
• Setup of log aggregation (EFK stack)
• VPC design and automated provisioning with terraform
• Secrets and certificate management
• Design and implementation of an ML data pipeline for image classification
• AWS lambda development (Python)
• Design and implementation of a multi-region Kubernetes cluster
• Design and implementation of a GitOps based CD pipeline based on ArgoCD
• Driving continuous security improvements, including threat modelling, establishment of secure coding best practices, vulnerability scanning, etc.
• Implementation security best practices for Kubernetes and AWS in general, e.g. AWS WAF, K8S network policies, etc.
• Regular training of the backend development team in topics like infrastructure as code and secure coding.
• Active participation as software engineer in a team of data scientists to teach and ensure software engineering best practices, including secure coding. Main focus was to ensure production readiness of Deep Learning based solutions / models created by the data science team.

• OpenShift installation and administration
• Deployment automation to OpenShift with Jenkins and Helm. Main focus was to stabilize a very complex deployment process, which was regularly unstable and prone to errors
• Development of cross-cutting application components (e.g. authentication, logging, etc.) in Java and AngularJS
• Development of microservices
• General system architecture consulting
• Performance engineering

• Installation and administration of OpenShift clusters
• Design and development of complex CD Pipelines with a strong security focus, including static code analysis, vulnerability scanning of third-party libraries (e.g. for OWASP top 10 vulnerabilities), container images, etc.
• Served as the interface between application development and Infrastructure Team, Collaboration with Dev and Ops teams
• Kafka cluster installation and administration
• Dockerization of applications, image hardening
• Development of automation scripts in Python, Bash and make
• Infrastructure automation
• Working with the dev team on cross-cutting concerns, such as Performance optimization, Security, Logging and Monitoring

• Besides specific projects conducted with DB Schenker, I was serving as Lead architect on an architecture department board, conducting research of new technology trends, establishing best practices in various areas of the SDLC, documenting results and regularly conduct presentations and training of the development team. The department in question comprised of ca. 450 developers in 4 regions (Germany, India, eastern Europe and China)
• This also included close cooperation with other departments in order to move towards company-wide standards and best practices

• VPC design and implementation
• Implementation of a fully automated installation of a production grade Kubernetes cluster in AWS, based on Ansible, Packer and Terraform
• Evaluation of OpenShift vs. plain Kubernetes
• Integration of Kubernetes with AWS autoscaling
• Installation of a logging solution for Kubernetes, based on the EFK stack
• Evaluation of multiple APM solutions (AppDynamics vs. DynaTrace vs. Instana)
• Installation of a monitoring solution for Kubernetes, based on Instana
• Kubernetes administration, including definition of various Kubernetes primitives
• Automation of infrastructure provisioning
• Automated configuration of various AWS resources, including RDS, Elastic Search Service and Elasticache
• Development of deployment pipelines
• Setup of an external caching layer
• Configuration of SSL/TLS
• Migration of multiple existing applications to the target platform (Docker/Kubernetes)
• Development of microservices in Java and Python
• Involvement in Ops activities according to DevOps principles

• Design and development of microservices based on a serverless architecture
• Development of infrastructure automation processes
• Development of a continuous deployment pipeline
• Coaching of an offshore team in China (10 developers)

• Design and implement application infrastructure (WebSphere Cluster on Linux, etc.)
• Automate deployment pipelines (Jenkins)
• Design of the application architecture
• Selection of technologies
• Design and implementation of critical components, e.g. an audit logging solution
• Design and implementation of system integrations
• Implementation of custom data migrations (ETL) for existing systems to be replaced, applying functional programming paradigms (in Clojure)

(Project did not include implementation, only a POC prototype)

• Design of a reference architecture for a global, harmonized/centralized eBusiness platform.
• Development of a prototype solution, The main goal was to enable support of varying requirements of different countries / regions and to enable efficient development with highly distributed teams
• Elicitation of architectural requirements
• Collaboration with stakeholders at different levels

• Design of application and integration architecture
• Requirements engineering
• Technical leadership of distributed development team
• Development of application and integration components