Amazon RDS Experts in Cologne

• PHP 8.4
• Platform for prize draws: API-first approach with Symfony/API Platform
• API Platform 4.2 (REST, JWT, Doctrine/PostgreSQL, API documentation) plus AWS tools
• Symfony 7.3 for infrastructure, hosting, and subsequent operation on AWS with ECS
• Postgres
• AWS RDS, SQS, Fargate, RDS Postgres database, and AWS-SQS message queue
• Infrastructure management with Terraform
• After successful Terraform implementation, the next organizational step is to establish a GmbH

• Regulated environment within a German banking group (approx. 8,500 employees, hybrid cloud strategy).

• Responsible for operating, provisioning, and continuously securing business-critical platforms – including a GenAI chat application, a big data/AI platform, and data science workspaces based on Azure Virtual Desktops and VMs. Ownership of Azure DevOps projects for ShaiHulud and React2Shell, as well as BSI alerts – Security Operations improvements across the SDLC.

• Deployment responsibility for the GenAI chat application, big data/AI platform (BDAI), and data science workspaces (AVD/VM-based) in the respective landing zones.

• Deployment & release management: end-to-end responsibility for deploying portal and service applications across multiple Azure landing zones, including technical approvals, compliance with development team deployment guidelines, and ensuring ITIL-based change and release processes via ServiceNow.

• Azure landing zones & network architecture: design, provisioning, and operation of Azure landing zones for 3-tier web applications with enhanced network segmentation, VNet peering, hub-and-spoke architectures, private endpoints, and firewall integration across separate subscriptions and tenants.

• Azure DevOps governance & operations: ownership of the Azure DevOps organization, including projects, repositories, and CI/CD pipelines; implementation of governance requirements such as branch policies, approval gates, permission models, and audit-ready operating structures.

• Infrastructure as Code (Terraform): design, implementation, and operation of a modular Terraform architecture for standardized cloud infrastructure deployment, including state management, provider versioning, reusability, and policy-as-code approaches.

• CI/CD pipeline engineering: design, operation, and optimization of complex YAML-based CI/CD pipelines with multi-stage deployments, template standardization, self-hosted agents, integrated secret management, and automated quality and security checks.

• Git migration & platform consolidation: planning and execution of repository and pipeline migration from Azure DevOps to GitLab CI/CD, including automated scripts, full Git history transfer, pipeline porting, and platform consolidation.

• Container & platform operations (AKS): operation and security assessment of containerized workloads on Azure Kubernetes Service, centralization of on-premises container registries for ACR.

• OpenShift (OCP) security reviews: security assessment of code baselines, build pipelines, and deployment processes for on-premises OpenShift clusters with critical applications, and derivation of specific hardening recommendations.

• Shift-left security & DevSecOps transformation: introduction of a company-wide shift-left approach for early security integration in development and deployment processes, enabling developers to perform self-led security checks and sustainably reduce vulnerabilities before production (IDE integrations, pre-commit hooks, local scanners).

• Software supply chain security: analysis and mitigation of supply chain risks in NPM- and Yarn-based applications through dependency audits, CI/CD pipeline hardening, token rotation, and restriction of risky build and lifecycle mechanisms.

• Frontend & framework security (React / Next.js): security assessment and coordination of critical vulnerability remediation across platform applications and web frameworks, including coordination and complementary technical mitigations with all teams following BSI alerts.

• Software composition analysis (SCA): introduction and operation of automated vulnerability scans for container images, pipelines/artifacts, and third-party dependencies, including SBOM exports within CI/CD pipelines.

• SAST/DAST integration: design and piloting of static and dynamic application security tests in close collaboration with security architecture and development teams, for continuous improvement of code and runtime security, and establishing operational acceptance tests.

• Artifact & registry consolidation: analysis and consolidation of all package and container repositories for service applications and AKS workloads, aiming for a centralized, secured registry strategy with centralized vulnerability scanning and governance.

• Dependency-Track & SBOM strategy: advising the compliance board on introducing a central SBOM and vulnerability management platform to increase enterprise-wide dependency transparency and accelerate CVE response capability.

• CI/CD pipeline hardening: security analysis and cleanup of the existing pipeline landscape by removing unused pipelines, improving secrets hygiene, implementing least-privilege principles, and isolating build agent environments.

• Azure Web Application Firewall (WAF) optimization: analysis and tuning of existing Azure WAF rules (OWASP Top 10 Core Rule Set, DSR/SDC, custom rules) to defend against known vulnerabilities and exploit patterns, including reducing false positives and improving threat detection.

• Documentation & stakeholder communication: creating and maintaining technical documentation, runbooks, and architecture overviews in Jira and Confluence, as well as active knowledge transfer between operations, development, security, and compliance stakeholders.

• Implementation of Infrastructure as Code (IaC) with Terraform to ensure a scalable, repeatable, and secure Azure infrastructure
• Implementation and optimization of CI/CD pipelines with Azure DevOps
• Management of container and server environments and AKS

Consulting, designing, and implementing the software testing lifecycle for multiple Android apps and backends Introducing test automation with Appium, SpringBootTest, RestAssured Setting up and managing emulators Developing an E2E library, an integration library, a Testcontainers library, and other libraries Developing, implementing, and advising on CI strategies Building the test environment with Testcontainers and virtualization Developing and implementing test cases for integration tests and end-to-end tests Establishing a maintainable test architecture with low entry barriers to simplify the creation of automated tests Some tools and technologies used: JUnit, RestAssured, Testcontainers, Kubedock, Appium, Android emulator, Jira Xray, Mockito, WireMock, Spring Framework, Kotlin

• Delivered AWS-authorized content through AAI program
• Facilitated group and 1-on-1 mentorship sessions
• Coached non-technical learners into cloud career paths
• Created learning materials aligned with AWS Skill Builder and AWS Academy labs

• Designed and led the development of an automated short-video generation system.
• Built a scalable AWS backend using Step Functions, Lambda, S3, ECS Fargate, and DynamoDB.
• Developed video rendering with OpenCV and FFMPEG; ensured maintainable Python code.
• Supervised and mentored a Python developer and trained the client in AI workflows.
• Decreased end-to-end production time from hours to minutes.
• Created a modular, extensible architecture designed to support future AI models.

• Designed and deployed a cloud-based grocery list app using AWS EC2 for hosting and RDS for persistent data storage, achieving 99.9% uptime across all test environments
• Reduced average response time by 2× through efficient deployment logic and optimized database queries, resulting in a smoother user experience across devices
• Utilized AWS (EC2, S3, RDS, IAM), Azure basics, Terraform, CloudFormation, Docker, Kubernetes basics, Jenkins, GitHub Actions, TCP/IP, DNS, Python, Bash scripting

• Developed automated ETL pipelines with AWS Glue and Athena to ensure consistent data quality and governance requirements
• Implemented validation, anonymization, and encryption measures for data in compliance with GDPR
• Optimized cloud costs by introducing FinOps practices and increased transparency for business units
• Monitored performance, performed root cause analyses, and ensured adherence to SLAs
• Supported data and solution architects in building scalable data models for ML and analytics scenarios