21.04.2026 aktualisiert

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Cloud | DevOps | Backend | Data | Security | https://cloud-force.net

Berlin, Deutschland
Weltweit
Master of Science
Berlin, Deutschland
Weltweit
Master of Science

Profilanlagen

cv_fabian_frank_en.pdf
cv_fabian_frank_de.pdf

Über mich

Cloud Engineer & Software Developer with 7+ years building scalable, secure cloud solutions. Expert in AWS, Azure, GCP, DevOps, IaC, CI/CD, microservices, and backend systems (Python). Proven results: up to 82% cost reduction, 80% efficiency gains, strong cloud security.

Skills

InnovationClean CodeSql Data WarehouseAPIsAgile MethodologieKünstliche IntelligenzAmazon Web ServicesAutomatisierungTest AutomationMicrosoft AzureBash ShellCloud ComputingCloud-SicherheitCloud DatabaseCloud-EngineeringCloud-ServerCloud-SpeicherContinuous IntegrationData ArchitectureDateninfrastrukturData IntegrationDevOpsAmazon DynamoDBTraceabilityGitHubSkalierbarkeitInfrastrukturPythonPostgreSQLLua ScriptingMongoDBMySQLSQL Server Management StudioNoSQLScrumSoftware ArchitectureRedisCloud-ServicesAnsibleScalaShell-ScriptSoftware-BereitstellungSoftware SystemsSQLSalesforce TableauYAMLAWS CDKS3 BucketDocker ContainerGoogle CloudCloud PlatformFlaskLarge Language ModelsGrafanaApache SparkMysql DatabasesInfrastructure as Code (IaC)BackendAWS ECSGitLabFastAPIKanbanBackend-programmierungPytestContainerisierungGitlab-CiAWS AuroraKubernetesInfrastrukturautomatisierungs-FrameworksDeployment AutomationAWS GlueAWS FargateAtlassian BitbucketMysql5Cloud IntegrationApi DesignCloudwatchApi-GatewayGestaltung der InfrastrukturSicherheitsbestimmungenTerraformServerless ComputingAWS EKSDockerMicroservices
Experienced Cloud Engineer and Software Developer with more than 7 years of extensive expertise in designing, developing, and deploying scalable, secure, and efficient cloud solutions. Specialized in Cloud Computing (AWS, Azure, GCP), DevOps practices, Infrastructure as Code (IaC), and automation of software deployment processes (CI/CD).

Long-standing experience in backend development, microservice architectures, CI/CD pipeline management, data integration, and cloud security. Strong expertise in agile methodologies (Scrum, Kanban) and collaborating with interdisciplinary teams to develop innovative, mission-critical software solutions.

Proven ability to reduce operational costs (~82%), increase efficiency and scalability (~80%), and improve security through modern cloud technologies and automated testing and deployment strategies.

Sprachen

DeutschMutterspracheEnglischverhandlungssicher

Projekthistorie

Native Dashboard Maintenance & Weiterentwicklung (AWS Data Pipelines & Tableau) – Senior Data Engineer & Cloud Engineer

Media Impact, Berlin

Marketing, PR und Design

250-500 Mitarbeiter

  1. Pflege, Betrieb und Weiterentwicklung von AWS Step Functions zur Orchestrierung komplexer ETL-Prozesse für mehrere Werbeplattformen (u. a. LinkedIn, Snapchat, Pinterest)
  2. Entwicklung, Wartung und Anpassung von AWS Lambda Functions in Python bei Änderungen an Quell-APIs, Datenmodellen oder Authentifizierungsverfahren
  3. Überwachung und Fehlerbehebung der Datenpipelines inkl. strukturierter Logs, automatischer Retry-Mechanismen und Alarmierung
  4. Qualitätssicherung der verarbeiteten Daten zur korrekten Darstellung von KPIs und Metriken in Tableau Dashboards
  5. Analyse und Optimierung bestehender Python-basierter Datenverarbeitung zur Verbesserung von Performance, Stabilität und Wartbarkeit
  6. Dokumentation der Prozesse und Übergabe von Betriebswissen zur nachhaltigen Weiterentwicklung des Systems

Highly Available Scalable Microservice Optimization System – Senior Python Developer, Cloud Architect & DevOps Engineer

EUROGATE

Transport und Logistik

500-1000 Mitarbeiter

  1. Set up a monorepo with uv, pre-commit hooks, type checking via MyPy, and linting via Ruff
  2. Designed and implemented decoupled microservices, ensuring high maintainability and independent scalability
  3. Utilized AWS SQS as a message queue for event-driven communication to increase system resilience and efficiently handle traffic spikes
  4. Implemented a “worker-pool” model for long-running solvers on ECS to eliminate cold start latency and ensure adherence to a strict 2-minute SLA for optimization jobs
  5. Built a Postgres database in Aurora Serverless V2, managed schema with SQLAlchemy, and performed migrations using Alembic
  6. Configured Redis cache in ElastiCache, atomizing actions with LUA scripts
  7. Applied Pydantic for strict validation of API requests and inter-service data exchange
  8. Ensured high test coverage through extensive unit and integration tests with Pytest, moto, and LocalStack to simulate AWS services
  9. Set up CI/CD pipelines in Bitbucket for automated testing, linting, and deployments
  10. Optimized system performance and reliability through modular architecture and asynchronous processing

LLM-Based Exam Question Generation System – Backend Developer & AI Integration Specialist

Cloud-Force

Internet und Informationstechnologie

< 10 Mitarbeiter

  1. Built a layered architecture with Service, Repository, and Domain layers for clean code structure and high testability
  2. Processed LLM requests asynchronously, increasing question generation efficiency by ~90%
  3. Applied Pydantic to validate and ensure integrity of generated questions
  4. Developed a transactional database system with SQLAlchemy for reliable storage and categorization of questions
  5. Optimized LLM outputs with prompt templates tailored to different medical specialties
  6. Built a PDF extraction module for automated processing of medical case text inputs
  7. Implemented domain-specific error handling for improved fault diagnosis
  8. Modularized the system to allow easy addition of new LLM providers and data sources
  9. Managed source code with Git to ensure traceable and efficient version control

LLM-Based Chatbot Development – Cloud Architect, AI Lead Engineer & DevOps Lead

Media Impact, Berlin

Medien und Verlage

250-500 Mitarbeiter

  1. Developed a Python-based chatbot using the Microsoft Bot Framework with RAG to enhance internal knowledge access
  2. Integrated ChatGPT via Azure OpenAI in a multi-stage LLM pipeline (Condense, Chunk, Classify, Compose) for precise, context-aware responses
  3. Designed and deployed a cloud-native microservices architecture using AWS Lambda, Kubernetes (EKS), and API Gateway
  4. Implemented Infrastructure as Code (IaC) with Terraform and Ansible to automate AWS and Kubernetes resource deployment within GitLab CI/CD pipelines
  5. Ensured secure handling of Terraform states using GitLab Terraform States
  6. Managed Kubernetes clusters and application deployments via kubectl and Helm
  7. Secured secrets using GitLab Secrets for CI/CD injection when needed
  8. Set up monitoring and alerting with Grafana, Prometheus, and AWS CloudWatch for proactive scaling and cluster performance optimization
  9. Automated deployment of networking infrastructure including VPC, Load Balancer, and Security Groups with Terraform
  10. Applied Scrum and Kanban for sprint planning, backlog management, and agile development
  11. Developed and maintained unit and integration tests using pytest and unittest integrated into CI/CD
  12. Version-controlled code with Git and maintained comprehensive documentation for ongoing development

Real-Time Anomaly Alert System – Cloud Architect & DevOps Lead

National News Media & Tech

Internet und Informationstechnologie

250-500 Mitarbeiter

  1. Designed and implemented a real-time data pipeline to monitor ad delivery using Kafka (MSK), AWS Timestream, and Go
  2. Developed stream-processing applications to detect anomalies with millisecond-level latency
  3. Built an automated alerting system using Microsoft Teams and AWS SNS for instant anomaly notifications
  4. Optimized event-driven architecture to reduce detection time of performance issues and improve SLA compliance
  5. Managed and configured Kubernetes deployments using kubectl and Helm
  6. Applied Scrum/Kanban principles for iterative development and continuous improvement
  7. Implemented CI/CD pipelines via GitHub Actions using YAML, integrating end-to-end tests with pytest and Selenium
  8. Version-controlled code with Git and documented all systems and processes for maintainability

Zertifikate

AWS Certified Solutions Architect – Associate

Amazon Web Services Training and Certification

2026

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