AWS Certified Solutions Architect – Associate

Led the end-to-end integration and migration architecture for decommissioning SAP IS-U market communication and transitioning to Salesforce Marketing Cloud (SFMC) with E.ON IT Services — covering regulated EDIFACT market messaging, a three-phase data migration (transfer of market message inventory after cutover), redesign of market communication processes, and full GDPR and German energy-market compliance.

• Designed the three-tier target architecture (SAP IS-U → NScale B2B gateway → SFMC) processing 50,000–100,000 EDIFACT messages daily within sub-5-minute SLAs.
• Architected the three-phase data migration: 36 months of historical data, zero-loss cutover of in-flight market messages, and near-real-time CDC synchronization.
• Delivered secure, BDEW/GDPR-compliant integration (AS2/OFTP2, RFC/IDoc, REST APIs, OAuth 2.0, Azure AD, AWS S3) achieving >99.5% uptime, <0.1% migration discrepancy, and RTO <4 hours.
• Applied BPMN to model and optimize the market communication processes.

Technologies: SAP IS-U, NScale, Salesforce Marketing Cloud, EDIFACT, OAuth 2.0, Azure AD, AWS S3, BPMN, Jira, Confluence, Draw.io

• Focus: System architecture, cloud-native platforms, microservices, API design
• Product: Pflege-Pfad is a digital placement platform that directly connects relatives of people in need of care with verified care services and caregivers – without an agency and without ongoing fees.
• Business analysis & process design:
• Analysis of the German care market and identification of the key pain points of both target groups.
• Modeling of core business processes: registration, verification, care request, application, placement, and rating.
• Definition of the business model as a freemium/premium model with optional contact unlocking.
• Creation of user stories and requirements documentation for relatives, care services, and administrators.
• Design of trust and quality assurance mechanisms with document upload, admin review process, and rating system.
• Coordination with stakeholders and validation of product decisions with potential users.
• Technical implementation:
• Design and implementation of the entire platform architecture as the sole developer.
• Design and implementation of a REST API with Spring Boot and Kotlin, including JWT-based authentication.
• Development of the frontend as a single-page application with Angular 17.
• Implementation of the AWS infrastructure with EC2, RDS PostgreSQL, S3, CloudFront, and IAM.
• Document upload with AWS S3 using presigned URLs to verify care services.
• Email notifications via Resend API.
• AI-supported care service search via OpenAI API.
• Implementation of complete user flows such as registration, login, password reset, and the placement process.
• Development of an admin panel for user and care service management as well as analytics.
• CI/CD with GitHub Actions and containerized deployments with Docker.
• End-to-end tests with Playwright.

Technologies: Kotlin, Spring Boot 3, Spring Security, JWT, JPA/Hibernate, PostgreSQL, Angular 17, TypeScript, RxJS, AWS (EC2, ECS, S3, CloudFront CDN, RDS PostgreSQL, IAM), nginx, GitHub Actions, Playwright, Maven, Git, OpenAI API, Resend API, Docker, Scrum, i18n (DE/EN/TR), Kiro, feature flag architecture.

• Optimizing and accelera­tion of our Gitlab CI pipeline

• Conceptual work for the PoC of the Zero Trust system

• Extension of the policy-engine backend in Go

• Extension of the policy-testing mechanism in Python

• Architectural design of the PEP component of Zero Trust

• Documentation of the product

• Technologies: Zero Trust, Go, Python, Gitlab CI, Docker, JWT, Domain-Driven Design

IT consulting, analysis, architecture design, new and further development, code review, test automation, continuous integration, continuous delivery in backend and frontend areas for Automotive Project Instavalo.

Frontend:

• Implementation of UI components according to specifications, especially style guides and responsive design eith React and Typescript
• Component testing
• Code documentation
• CI/CD with Gitlab Pipeline

Backend / IoT:

• Analysis and architectural design with AWS Greengrass IoT on Edge Devices
• Setting up Microservices containers with Docker Compose on Edge device with AWS Greengrass and AWS IoT IAM, Token Exchange Service, Ansible
• CI/CD with Gitlab Pipeline, Terraform, AWS ECR
• Logging with Fluentbit Lua Language for AWS Cloudwatch
• Python Lambda for AWS Greengrass Recipe deployment on Edge Devices
• Implementation of test-driven development with JUnit, Mockito, and code Coverage
• Jacoco
• Definition of REST interfaces with OpenAPI / Swagger
• Development and enhancement of software based on Java Quarkus, Typescript NestJs NodeJs and Python
• Authentication and authorization in Aws IAM
• Development of REST and gRPC interfaces for the frontend and backend
• Implementation of Maven dependencies with DevSecOps OWASP
• Spring AI, Jetbrains AI Assistant, Junie, Github Copilot, Claude Code, Agents, Skills, Command, Hooks, Subagents

• Built and further developed an AWS landing zone based on Terraform / OpenTofu (multi-account structure, IAM baselines, network and security standards)
• Designed and operated platform-oriented AWS architectures to standardize infrastructure and operations processes
• Built and operated Kubernetes-based platforms (EKS) as a shared runtime environment for application teams
• Established GitOps-based deployments with Argo CD and FluxCD
• Developed and operated central CI/CD platforms (GitLab CI, GitHub Actions, Jenkins)
• Enabled development and project teams through reusable platform building blocks
• Introduced and implemented FinOps structures (AWS Cost Explorer, CUR + Athena, Infracost, Grafana dashboards)
• Built and operated central observability platforms (Prometheus, Grafana, Loki, Alertmanager, CloudWatch)

• Error analysis and fixes including performance optimization of the in-house developed platform API
• Change and incident management in day-to-day operations
• Responsible for compliance with security and compliance requirements
• Vendor management for software development and maintenance
• Planning and execution of migration of legacy services to a cloud native platform

Role in the project: project staff, implementation team

Used skills: requirements analysis, IT service and application management, IT operations, error analysis and performance optimization, software maintenance and lifecycle management

Project environment: Cloud Native Platform (Kubernetes, Crossplane, AWS, ArgoCD, Grafana)

• Creation, maintenance and hardening of Kubernetes clusters employing Ansible and ArgoCD
• Keywords: Ansible, AWX, Kubernetes, NetApp, Prometheus, CI/CD ArgoCD, SSO, Fluent-bit, HAProxy, Calico, Keycloak, oauth2-proxy, SealedSecrets, kubeseal, Aqua kube-bench, CIS-Benchmarks, Aqua Trivy operator

• Understand the customer’s business & technical requirements and translate them into system / technical requirements
• Design and implement Schrodinger’s applications on cloud systems, and experience convincing senior management and senior technical staff of the benefits of their journey with Schrodinger on the cloud
• Provide exceptional technical design and thought leadership, especially around AWS, GCP, and K8s architecture reviews, performance, high availability, cost, and security
• Deep understanding of the Well-Architected pillars and all best practices for building a secure, performant Schrodinger’s applications on the cloud platforms
• Lead technical workshops and advise customers on architectural and strategic IT decisions
• Ensure success in designing, building and migrating applications, software, and services on the cloud platforms
• Educate customers on best practices to ensure their solutions are designed for successful deployment in the cloud
• Work with other team members to ensure quality and customer success
• Define the tickets, tasks, and timelines of projects
• Collaborate with account managers to ensure that the projects are executed according to the defined plan and timeline
• Monitor the progress of the projects, identify risks and issues, and take proactive measures to mitigate them
• Lead and inspire cloud architect teams, provide guidance, and make critical decisions
• Facilitate effective communication and collaboration among team members
• Collaborate with Schrodinger’s managers to improve deployment, support, and configuration of Schrodinger’s applications
• Lead weekly standups and define priorities

OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.

Clients: CARIAD, AUDI AG

• Built and deployed enterprise MLOps pipelines using Azure Machine Learning and Databricks. Reduced model release cycles by 95 percent, from four weeks to two days, through automated CI CD workflows.
• Delivered cloud native DevOps platforms for ADAS programs using Azure data services, Kubernetes, and Terraform based infrastructure provisioning.
• Designed high availability architectures with automated failover. Cut system downtime by 85 percent for mission critical energy trading platforms.
• Developed and integrated AI agents and enterprise chatbots using LangChain, AutoGPT, and GPT models. Enabled autonomous workflows and decision driven automation.
• Reduced cloud infrastructure spend by 40 percent through autoscaling strategies, spot instance usage, and policy driven resource governance across Azure and AWS.
• Partnered with Data Scientists, ML Engineers, Product Managers, and executive stakeholders to deliver large scale automotive and energy solutions.
• Implemented GitOps driven CI CD pipelines supporting automotive software delivery for over 500 engineers across distributed product teams.
• Designed and operated Kubernetes platforms on Azure AKS. Improved deployment stability and reduced rollback events by 70 percent.
• Implemented observability and monitoring stacks using Prometheus, Grafana, and Azure Monitor. Achieved 99.9 percent service availability targets.

• Create an AI legal assistant with modern ML capabilities.
• Implement RAG architecture, with data pipelines for legal data search.
• Use AWS Bedrock for LLM and embedding models and LangChain/LangGraph
• Python with FastApi for backend and React for frontend

• Designed and implemented end-to-end data pipelines (batch & streaming) using Python, SQL, and Apache Spark, Databricks on AWS reducing ETL latency by 40%.
• Developed serverless event-driven ingestion pipelines using AWS Lambda and SQS, ensuring real-time data availability for downstream analytics.
• Leveraged Google Cloud Platform (GCP) services including BigQuery and Dataflow to manage cross-cloud data warehousing and analytics integration.
• Expertise in DMS (CDC, Full Load) and Airflow for scalable data pipeline automation and orchestration.
• Managed and customized data pipelines using Databricks, Airflow. Automation using Docker, Kubernetes, Terraform.
• Automated data quality checks using dbt to modularize transformations and ensure production-grade data lineage, improving reliability by 30%.
• Collaborated with compliance teams to ensure GDPR and SOC2 alignment. Mentored junior engineers and contributed to architecture refactoring for scalability.
• Created and maintained dashboards in Power BI to provide actionable insights.

• Migration of backups and complete workloads to AWS and Azure, including setup and management of AKS & EKS clusters.
• Automation with Terraform & ArgoCD, CI/CD pipelines implemented with GitLab.
• System monitoring on OpenShift 4 (on-premise) with Grafana & Prometheus, use of CloudWatch and X-Ray for analysis and logging.
• Building and maintaining secure network infrastructures (VPCs, SGs, WAF, ACLs), integration of Azure Log Analytics.
• Close collaboration with infrastructure and development teams, maintenance of technical documentation with Confluence, ticket handling via Jira, and promoting cloud knowledge within the company.