Hire the best Platform Engineers in Germany matched in minutes from over 15,000 CVs with the power of AI
Accelerate your software delivery with experts in Kubernetes, Terraform, AWS, and internal developer platforms. We match your project with vetted, available freelance infrastructure specialists quickly and precisely.
About the role
Designing Internal Developer Platforms
Platform engineering focuses on building internal developer platforms to accelerate software delivery. These specialists design self-service portals, automated pipelines, and standard templates that hide infrastructure complexity from product developers. By establishing these Golden Paths, they eliminate friction in the deployment process and allow engineering teams to release software autonomously and securely.
Core Technology Stack and Skills
Successful experts in this field possess deep knowledge of cloud-native ecosystems, automation tools, and container orchestration. They integrate diverse systems into a unified internal platform that supports rapid, repeatable deployments.
- Container orchestration with Kubernetes and Docker
- Infrastructure as Code using Terraform, Ansible, or Pulumi
- CI/CD pipeline automation with GitLab CI, GitHub Actions, or Jenkins
- Cloud administration across AWS, Azure, and Google Cloud Platform
- Monitoring, observability, and logging with Prometheus, Grafana, and ELK
Driving Engineering Efficiency in Germany
Many companies in Germany, from manufacturing giants adopting Industry 4.0 to fast-growing digital startups, face a shortage of cloud infrastructure talent. Freelance experts help local engineering teams standardize their cloud environments and comply with strict European data regulations. By introducing scalable self-service platforms, they help organizations modernize legacy infrastructure while ensuring that development teams can focus on core product features.
When to Onboard a Freelance Platform Specialist
Organizations bring in freelance platform architects to bridge immediate skills gaps during cloud migrations or DevOps transformations. Hiring an external expert makes sense when internal teams are overwhelmed by provisioning requests or when product deployments are delayed by manual operations. A freelancer provides the immediate, high-level expertise needed to design the initial platform architecture, train permanent staff, and establish reliable automation practices without long-term overhead.
Meet FRATCH Platform Engineers
Ali Aminian
Enterprise Software Architect | Cloud, Integration & AI Platforms
Last position:
Platform Engineer & Software Architect at Yatta GmbH
- Architected the Yatta Integration Layer – a config-driven integration platform on Java 25, Spring Boot 4 (WebFlux), Temporal, gRPC and Kafka, enabling new third-party integrations (e.g. AVS fulfillment) via declarative JSON configs with zero code changes.
- Designed and implemented Tink integration with 0Auth IBAN verification to enhance fraud prevention and account validation workflows with Adyen payByBank.
- Architected and implemented an OpenFGA-based authorization model for centralized management of users, groups, and fine-grained access control in the vendor portal.
- Architected and led delivery of the Yatta API Gateway platform using GraphQL Federation, providing a unified enterprise API layer across distributed microservices with centralized authentication, authorization and request orchestration.
- Replaced NGINX + NLB with Istio service mesh and AWS ALB; rolled out WAF, OAuth (Cognito), IP whitelisting and RBAC across environments.
- Migrated CDC from Confluent Cloud connectors to a self-hosted Kafka Connect + Debezium stack, reducing operational cost by ~80% across multiple environments.
- Implemented the Transactional Outbox pattern with Debezium for reliable, exactly-once event publishing to Kafka with Avro and Schema Registry.
- Migrated dunning/payment-recovery workflows from Airflow to Temporal, achieving 99.9% reliability for settlement handling.
- Optimised Apache Airflow with deferrable sensors to handle 1000+ concurrent DAG runs without scaling the worker pool.
- Refactored a monolithic Terraform codebase into 3 modular projects, cutting deployment time by ~45%.
- Stood up full observability with OpenTelemetry, Tempo, Prometheus and Loki; automated dev/staging/prod with ArgoCD, Image Updater and Helm.
- Collaborated with product, operations and engineering stakeholders to define scalable platform architecture and integration standards aligned with long-term business and operational goals.
Kiriakos Krastillis
Platform Engineering Tech Lead / Architect
Last position:
Tech Lead / Architect : OTTO API Platform at OTTO
maturing their API Practices on both, a Business and Technology level. My role encompasses strategy, architecture, developer advocacy as well as hands on software engineering, enabling both technical teams and business leadership to adopt and act on API- centric principles effectively. Coincidentally, we also establish GitOps, DX and Platform Best practices with this project.
Highlights:
- Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
- Formulating a way forward for API Lifecycle Management at OTTO
- Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals
API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, react, nodejs, typescript, redocly, reactive programming, CDC, golang, gingonic, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
Kiriakos Krastillis
Platform Engineering Tech Lead / Architect
Last position:
Tech Lead / Architect : OTTO API Platform at OTTO
maturing their API Practices on both, a Business and Technology level. My role encompasses strategy, architecture, developer advocacy as well as hands on software engineering, enabling both technical teams and business leadership to adopt and act on API- centric principles effectively. Coincidentally, we also establish GitOps, DX and Platform Best practices
maturing their API Practices on both, a Business and Technology level. My role encompasses strategy, architecture, developer advocacy as well as hands on software engineering, enabling both technical teams and business leadership to adopt and act on API- centric principles effectively. Coincidentally, we also establish GitOps, DX and Platform Best practices with this project.
Highlights:
- Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
- Formulating a way forward for API Lifecycle Management at OTTO
- Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals
API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, react, nodejs, typescript, redocly, reactive programming, CDC, golang, gingonic, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
with this project.
Highlights:
- Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
- Formulating a way forward for API Lifecycle Management at OTTO
- Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals
API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, react, nodejs, typescript, redocly, reactive programming, CDC, golang, gingonic, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
Nemanja Milenković
Senior / Lead AI Engineer | Applied GenAI, RAG, AI Agents & AI Platform Engineering
Last position:
AI Engineer / Senior Backend Engineer at Intelycx
Manufacturing intelligence platform with enterprise workflows, RAG, real-time AI assistant features, and multi-repository backend architecture.
- Built and extended production AI/backend services with Django, DRF, FastAPI, GraphQL, Celery, PostgreSQL, MySQL, Redis, and WebSockets across a modular multi-repository platform.
- Contributed to ARIS V2, a real-time manufacturing AI assistant using LangChain, LangGraph, MCP tool orchestration, planning/execution flows, OpenAI, AWS Bedrock, Qdrant, and Elasticsearch/OpenSearch-backed retrieval.
- Supported rollout expansion from ARIS V1 in 4 of 17 client production plants to ARIS V2 currently active in 13 of 17 plants, increasing real-world deployment coverage to more than 50% of the client footprint.
- Worked on document-grounded RAG functionality including ingestion, OCR, chunking, embeddings, indexing, retrieval, reranking, and grounded answer generation for industrial workflows.
Stack: Python, Django, DRF, FastAPI, LangChain, LangGraph, GraphQL, Celery, WebSockets, OpenAI, AWS Bedrock, Qdrant, Elasticsearch/OpenSearch, PostgreSQL, MySQL, Redis, Docker.
Nemanja Milenković
Senior / Lead AI Engineer | Applied GenAI, RAG, AI Agents & AI Platform Engineering
Last position:
AI Engineer / Senior Backend Engineer at Intelycx
Manufacturing intelligence platform with enterprise workflows, RAG, real-time AI assistant features, and multi-repository backend architecture.
- Built and extended production AI/backend services with Django, DRF, FastAPI, GraphQL, Celery, PostgreSQL, MySQL, Redis, and WebSockets across a modular multi-repository platform.
Manufacturing intelligence platform with enterprise workflows, RAG, real-time AI assistant features, and multi-repository backend architecture.
- Built and extended production AI/backend services with Django, DRF, FastAPI, GraphQL, Celery, PostgreSQL, MySQL, Redis, and WebSockets across a modular multi-repository platform.
- Contributed to ARIS V2, a real-time manufacturing AI assistant using LangChain, LangGraph, MCP tool orchestration, planning/execution flows, OpenAI, AWS Bedrock, Qdrant, and Elasticsearch/OpenSearch-backed retrieval.
- Supported rollout expansion from ARIS V1 in 4 of 17 client production plants to ARIS V2 currently active in 13 of 17 plants, increasing real-world deployment coverage to more than 50% of the client footprint.
- Worked on document-grounded RAG functionality including ingestion, OCR, chunking, embeddings, indexing, retrieval, reranking, and grounded answer generation for industrial workflows.
Stack: Python, Django, DRF, FastAPI, LangChain, LangGraph, GraphQL, Celery, WebSockets, OpenAI, AWS Bedrock, Qdrant, Elasticsearch/OpenSearch, PostgreSQL, MySQL, Redis, Docker.
- Contributed to ARIS V2, a real-time manufacturing AI assistant using LangChain, LangGraph, MCP tool orchestration, planning/execution flows, OpenAI, AWS Bedrock, Qdrant, and Elasticsearch/OpenSearch-backed retrieval.
- Supported rollout expansion from ARIS V1 in 4 of 17 client production plants to ARIS V2 currently active in 13 of 17 plants, increasing real-world deployment coverage to more than 50% of the client footprint.
- Worked on document-grounded RAG functionality including ingestion, OCR, chunking, embeddings, indexing, retrieval, reranking, and grounded answer generation for industrial workflows.
Stack: Python, Django, DRF, FastAPI, LangChain, LangGraph, GraphQL, Celery, WebSockets, OpenAI, AWS Bedrock, Qdrant, Elasticsearch/OpenSearch, PostgreSQL, MySQL, Redis, Docker.
Deepak Mishra
Lead ML Platform Engineer
Last position:
Lead ML Platform Engineer at Billie GmbH
- Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
- Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
- Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
- Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
- Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
- Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
- Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
- Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
- Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
- Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices
Deepak Mishra
Lead ML Platform Engineer
Last position:
Lead ML Platform Engineer at Billie GmbH
- Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
- Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
- Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
- Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
- Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
- Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
- Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
- Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
- Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
- Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
- Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices
- Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
- Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
- Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
- Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
- Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
- Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
- Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
- Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
- Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices
Ariel Lev
Engineering Manager · AI Platform Architect · Cloud-Native Infrastructure
Last position:
Sr. Principal Engineer at Slalom
- Held direct line management responsibility for a team of 4 Platform Engineers — owning hiring, performance reviews, and career development — while establishing a shared engineering standards framework and coaching culture that accelerated delivery across client engagements.
- Led a team of engineers to architect a cloud-native voice AI system for a major inspection client, enabling 2,500 field inspectors to document work fully hands-free via real-time transcription and AI agents — eliminating manual data entry across 440,000 inspections per month and reducing per-user cost from $9 to $1. Stack: AWS (DynamoDB, S3, Transcribe, CloudFront, API Gateway, Bedrock), ElevenLabs, Claude.
- Led a team of engineers to automate multi-region Kubernetes cluster management for a global SaaS leader, reducing provisioning time from 3 weeks to under a day and eliminating 90% of configuration errors. Stack: EKS, Terragrunt, Python, Bash, ArgoCD.
- Accelerator - Cloud-Agnostic AI Platform: Architected and delivered a cloud-agnostic, Kubernetes-native platform as an accelerator, enabling multi-tenant, enterprise-scale management of self-hosted LLMs with concurrent deployment of multiple base models and dynamic LoRA adapter serving. Designed production infrastructure using open-source tooling (ArgoCD, Karpenter, vLLM, SGLang) with automated model lifecycle management, API security (Keycloak + LiteLLM), and cost-optimized GPU provisioning.
Ariel Lev
Engineering Manager · AI Platform Architect · Cloud-Native Infrastructure
Last position:
Sr. Principal Engineer at Slalom
- Held direct line management responsibility for a team of 4 Platform Engineers — owning hiring, performance reviews, and career development — while establishing a shared engineering standards framework and coaching culture that accelerated delivery across client engagements.
- Held direct line management responsibility for a team of 4 Platform Engineers — owning hiring, performance reviews, and career development — while establishing a shared engineering standards framework and coaching culture that accelerated delivery across client engagements.
- Led a team of engineers to architect a cloud-native voice AI system for a major inspection client, enabling 2,500 field inspectors to document work fully hands-free via real-time transcription and AI agents — eliminating manual data entry across 440,000 inspections per month and reducing per-user cost from $9 to $1. Stack: AWS (DynamoDB, S3, Transcribe, CloudFront, API Gateway, Bedrock), ElevenLabs, Claude.
- Led a team of engineers to automate multi-region Kubernetes cluster management for a global SaaS leader, reducing provisioning time from 3 weeks to under a day and eliminating 90% of configuration errors. Stack: EKS, Terragrunt, Python, Bash, ArgoCD.
- Accelerator - Cloud-Agnostic AI Platform: Architected and delivered a cloud-agnostic, Kubernetes-native platform as an accelerator, enabling multi-tenant, enterprise-scale management of self-hosted LLMs with concurrent deployment of multiple base models and dynamic LoRA adapter serving. Designed production infrastructure using open-source tooling (ArgoCD, Karpenter, vLLM, SGLang) with automated model lifecycle management, API security (Keycloak + LiteLLM), and cost-optimized GPU provisioning.
- Led a team of engineers to architect a cloud-native voice AI system for a major inspection client, enabling 2,500 field inspectors to document work fully hands-free via real-time transcription and AI agents — eliminating manual data entry across 440,000 inspections per month and reducing per-user cost from $9 to $1. Stack: AWS (DynamoDB, S3, Transcribe, CloudFront, API Gateway, Bedrock), ElevenLabs, Claude.
- Led a team of engineers to automate multi-region Kubernetes cluster management for a global SaaS leader, reducing provisioning time from 3 weeks to under a day and eliminating 90% of configuration errors. Stack: EKS, Terragrunt, Python, Bash, ArgoCD.
- Accelerator - Cloud-Agnostic AI Platform: Architected and delivered a cloud-agnostic, Kubernetes-native platform as an accelerator, enabling multi-tenant, enterprise-scale management of self-hosted LLMs with concurrent deployment of multiple base models and dynamic LoRA adapter serving. Designed production infrastructure using open-source tooling (ArgoCD, Karpenter, vLLM, SGLang) with automated model lifecycle management, API security (Keycloak + LiteLLM), and cost-optimized GPU provisioning.
Can Savastürk
Software Development for People
Last position:
Platform Engineer at ClimateChoice
In a lean, execution-focused environment, I took ownership beyond a narrow engineering lane, shaping and implementing systems across backend, data, and infrastructure. Partnered directly with the three founders in a fast-moving, high-stakes environment, turning strategic priorities into concrete technical decisions and production outcomes.
- Owned core platform development across backend (Django/Rest Framework/Postgres), ETL (Python/Dagster), infrastructure (Terraform/Kubernetes/AWS), and frontend (typescript/react) for a climate-tech SaaS product, driving continuous cross-stack development across five repositories from October 2021 to this day.
- Architected and owned a standalone internal Python scoring framework for CRC assessments, using YAML-driven rules and metaprogramming to enable non-technical users to define complex evaluation logic without hardcoded implementations.
- Built and stabilized ETL and scraping pipelines using Dagster and Scrapfly, improving document ingestion, tagging, retry behavior, deployment flow, and operational resilience.
- Contributed to platform modernization and reliability through Django/Python upgrades, Postgres/RDS and EKS changes, CDN/TLS updates, test and performance improvements, and observability hardening.
- Drove backend engineering for product features, translating requirements into technical specifications, API contracts, data structures, and scalable implementation plans.
Can Savastürk
Software Development for People
Last position:
Platform Engineer at ClimateChoice
In a lean, execution-focused environment, I took ownership beyond a narrow engineering lane, shaping and implementing systems across backend, data, and infrastructure. Partnered directly with the three founders in a fast-moving, high-stakes environment, turning strategic priorities into concrete technical decisions and production outcomes.
In a lean, execution-focused environment, I took ownership beyond a narrow engineering lane, shaping and implementing systems across backend, data, and infrastructure. Partnered directly with the three founders in a fast-moving, high-stakes environment, turning strategic priorities into concrete technical decisions and production outcomes.
- Owned core platform development across backend (Django/Rest Framework/Postgres), ETL (Python/Dagster), infrastructure (Terraform/Kubernetes/AWS), and frontend (typescript/react) for a climate-tech SaaS product, driving continuous cross-stack development across five repositories from October 2021 to this day.
- Architected and owned a standalone internal Python scoring framework for CRC assessments, using YAML-driven rules and metaprogramming to enable non-technical users to define complex evaluation logic without hardcoded implementations.
- Built and stabilized ETL and scraping pipelines using Dagster and Scrapfly, improving document ingestion, tagging, retry behavior, deployment flow, and operational resilience.
- Contributed to platform modernization and reliability through Django/Python upgrades, Postgres/RDS and EKS changes, CDN/TLS updates, test and performance improvements, and observability hardening.
- Drove backend engineering for product features, translating requirements into technical specifications, API contracts, data structures, and scalable implementation plans.
- Owned core platform development across backend (Django/Rest Framework/Postgres), ETL (Python/Dagster), infrastructure (Terraform/Kubernetes/AWS), and frontend (typescript/react) for a climate-tech SaaS product, driving continuous cross-stack development across five repositories from October 2021 to this day.
- Architected and owned a standalone internal Python scoring framework for CRC assessments, using YAML-driven rules and metaprogramming to enable non-technical users to define complex evaluation logic without hardcoded implementations.
- Built and stabilized ETL and scraping pipelines using Dagster and Scrapfly, improving document ingestion, tagging, retry behavior, deployment flow, and operational resilience.
- Contributed to platform modernization and reliability through Django/Python upgrades, Postgres/RDS and EKS changes, CDN/TLS updates, test and performance improvements, and observability hardening.
- Drove backend engineering for product features, translating requirements into technical specifications, API contracts, data structures, and scalable implementation plans.
Patrick Eichler
PROFESSIONAL IN GOOGLE CLOUD & KUBERNETES
Last position:
Honorary Lecturer at SRH University Berlin
- Cloud Computing Fundamentals & Architecture: Expertise in core cloud concepts, including the three main Service Models (IaaS, PaaS, SaaS) and diverse Deployment Models (Public, Private, Hybrid, Multi-cloud).
- Modern Application Deployment Strategies (GCP Focus): Instruction on the GCP Application Hosting Spectrum, covering Virtual Machines, Containers (Kubernetes and Cloud Run), Platform as a Service (App Engine), and Serverless Computing (Functions as a Service - FaaS).
- Data Management & Big Data Analytics: Comprehensive coverage of Cloud Storage options (Object, Block, File) and Database solutions, including Relational (Cloud SQL), NoSQL (Firestore, BigTable, Memorystore), and serverless enterprise data warehousing (BigQuery).
- DevOps and Infrastructure Automation: Skills in DevOps principles, including Continuous Integration (CI), Continuous Delivery (CD), Infrastructure as Code (IaC) using tools like Terraform, and implementing effective Monitoring and Logging for system observability.
- Emerging Technologies & Responsible Cloud Use: Focus on crucial topics like Cloud and IoT Security, Identity and Access Management (IAM), data privacy, and the ethical considerations of cloud and massive data collection.
Patrick Eichler
PROFESSIONAL IN GOOGLE CLOUD & KUBERNETES
Last position:
Honorary Lecturer at SRH University Berlin
- Cloud Computing Fundamentals & Architecture: Expertise in core cloud concepts, including the three main Service Models (IaaS, PaaS, SaaS) and diverse Deployment Models (Public, Private, Hybrid, Multi-cloud).
- Cloud Computing Fundamentals & Architecture: Expertise in core cloud concepts, including the three main Service Models (IaaS, PaaS, SaaS) and diverse Deployment Models (Public, Private, Hybrid, Multi-cloud).
- Modern Application Deployment Strategies (GCP Focus): Instruction on the GCP Application Hosting Spectrum, covering Virtual Machines, Containers (Kubernetes and Cloud Run), Platform as a Service (App Engine), and Serverless Computing (Functions as a Service - FaaS).
- Data Management & Big Data Analytics: Comprehensive coverage of Cloud Storage options (Object, Block, File) and Database solutions, including Relational (Cloud SQL), NoSQL (Firestore, BigTable, Memorystore), and serverless enterprise data warehousing (BigQuery).
- DevOps and Infrastructure Automation: Skills in DevOps principles, including Continuous Integration (CI), Continuous Delivery (CD), Infrastructure as Code (IaC) using tools like Terraform, and implementing effective Monitoring and Logging for system observability.
- Emerging Technologies & Responsible Cloud Use: Focus on crucial topics like Cloud and IoT Security, Identity and Access Management (IAM), data privacy, and the ethical considerations of cloud and massive data collection.
- Modern Application Deployment Strategies (GCP Focus): Instruction on the GCP Application Hosting Spectrum, covering Virtual Machines, Containers (Kubernetes and Cloud Run), Platform as a Service (App Engine), and Serverless Computing (Functions as a Service - FaaS).
- Data Management & Big Data Analytics: Comprehensive coverage of Cloud Storage options (Object, Block, File) and Database solutions, including Relational (Cloud SQL), NoSQL (Firestore, BigTable, Memorystore), and serverless enterprise data warehousing (BigQuery).
- DevOps and Infrastructure Automation: Skills in DevOps principles, including Continuous Integration (CI), Continuous Delivery (CD), Infrastructure as Code (IaC) using tools like Terraform, and implementing effective Monitoring and Logging for system observability.
- Emerging Technologies & Responsible Cloud Use: Focus on crucial topics like Cloud and IoT Security, Identity and Access Management (IAM), data privacy, and the ethical considerations of cloud and massive data collection.
Alexander Gottschlich
DevOps / Platform Engineer
Last position:
DevOps / Platform Engineer at Cologne Intelligence GmbH
- Built and operated an AWS Landing Zone with 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 developer and project teams with reusable platform components
- Introduced and implemented FinOps structures (AWS Cost Explorer, CUR + Athena, Infracost, Grafana dashboards)
- Built and operated central observability platforms (Prometheus, Grafana, Loki, Alertmanager, CloudWatch)
Alexander Gottschlich
DevOps / Platform Engineer
Last position:
DevOps / Platform Engineer at Cologne Intelligence GmbH
- Built and operated an AWS Landing Zone with 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 an AWS Landing Zone with 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 developer and project teams with reusable platform components
- Introduced and implemented FinOps structures (AWS Cost Explorer, CUR + Athena, Infracost, Grafana dashboards)
- Built and operated central observability platforms (Prometheus, Grafana, Loki, Alertmanager, CloudWatch)
- 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 developer and project teams with reusable platform components
- Introduced and implemented FinOps structures (AWS Cost Explorer, CUR + Athena, Infracost, Grafana dashboards)
- Built and operated central observability platforms (Prometheus, Grafana, Loki, Alertmanager, CloudWatch)
Fayyaz Ilyas
Senior / Global IT Project Manager, Cloud & Platform Engineering
Last position:
Senior / Global IT Project Manager, Cloud & Platform Engineering at BOSCH
- Led multiple concurrent, enterprise-scale technical programs spanning backend services, APIs, identity platforms, cloud infrastructure, and security
- Actively participated in system architecture and design reviews, validating service interactions, data flows, security models, and scalability requirements
- Worked hands-on with engineering teams to decompose complex initiatives into technical epics, stories, and deliverables
- Reviewed technical approaches, migration strategies, and rollout plans to minimize operational and security risk
- Delivered SSO, MFA, directory services, SaaS integrations, and platform modernization impacting tens of thousands of users globally
- Drove Agile delivery across globally distributed teams; facilitated ceremonies, resolved blockers, and improved engineering throughput
- Established technical RAID logs, dependency maps, and milestone-based execution plans in regulated enterprise environments
- Acted as a trusted technical partner to senior leadership, translating complex engineering topics into business-relevant outcomes
Fayyaz Ilyas
Senior / Global IT Project Manager, Cloud & Platform Engineering
Last position:
Senior / Global IT Project Manager, Cloud & Platform Engineering at BOSCH
- Led multiple concurrent, enterprise-scale technical programs spanning backend services, APIs, identity platforms, cloud infrastructure, and security
- Actively participated in system architecture and design reviews, validating service interactions, data flows, security models, and scalability requirements
- Led multiple concurrent, enterprise-scale technical programs spanning backend services, APIs, identity platforms, cloud infrastructure, and security
- Actively participated in system architecture and design reviews, validating service interactions, data flows, security models, and scalability requirements
- Worked hands-on with engineering teams to decompose complex initiatives into technical epics, stories, and deliverables
- Reviewed technical approaches, migration strategies, and rollout plans to minimize operational and security risk
- Delivered SSO, MFA, directory services, SaaS integrations, and platform modernization impacting tens of thousands of users globally
- Drove Agile delivery across globally distributed teams; facilitated ceremonies, resolved blockers, and improved engineering throughput
- Established technical RAID logs, dependency maps, and milestone-based execution plans in regulated enterprise environments
- Acted as a trusted technical partner to senior leadership, translating complex engineering topics into business-relevant outcomes
- Worked hands-on with engineering teams to decompose complex initiatives into technical epics, stories, and deliverables
- Reviewed technical approaches, migration strategies, and rollout plans to minimize operational and security risk
- Delivered SSO, MFA, directory services, SaaS integrations, and platform modernization impacting tens of thousands of users globally
- Drove Agile delivery across globally distributed teams; facilitated ceremonies, resolved blockers, and improved engineering throughput
- Established technical RAID logs, dependency maps, and milestone-based execution plans in regulated enterprise environments
- Acted as a trusted technical partner to senior leadership, translating complex engineering topics into business-relevant outcomes
Alexander Vasiliev
Software Architect / Software Engineer / Tech Lead
Last position:
Senior DevOps / Platform Engineer at Kaufland e-commerce / real.digital (ex hitmeister.de)
- Evolved the platform from bare-metal infrastructure with a monolithic PHP application to a hybrid Google Cloud architecture with Go microservices on Kubernetes
- Managed and scaled a production infrastructure with 300+ VMs and dozens of clusters, including MySQL, PostgreSQL, MongoDB, RabbitMQ, Redis and Elasticsearch clusters
- Designed architecture, deployment, monitoring, performance analysis, and upgrades for all platform services using Terraform and Ansible
- Migrated observability systems from ELK and Prometheus to Datadog, managed with Terraform
- Introduced Jenkins CI/CD with SonarQube integration and automated tests to speed up feedback cycles
- Containerized the testing environment and implemented GitLab CI pipelines for Docker image builds, static code analysis, and infrastructure tests
- Performed zero-downtime migrations of MySQL and MongoDB clusters to Google Cloud
- Developed reusable Ansible roles for database clusters and automated data obfuscation for staging environments
- Decomposed monolithic databases and migrated to microservice architectures
- Built tools to detect and optimize slow queries in MySQL and MongoDB
- Conducted online schema migrations with pt-online-schema-change without downtime windows
- Developed internal Go applications for batch queries, GitLab-Jira integration, and MongoDB backup recovery
- Technologies: Debian, Ubuntu, Alpine, Go, Bash, Python, PHP, SQL, GitLab CI, Jenkins, Drone CI, MySQL, MongoDB, PostgreSQL, Redis, Elasticsearch, RabbitMQ, Kafka, Docker, Kubernetes, Nomad, Ansible, Terraform, Grafana, ELK, Prometheus, Datadog, Nagios, Zabbix, Nginx, HAProxy, Vault, Helm, SonarQube, Filebeat, Auditbeat, Google Cloud, AWS
Alexander Vasiliev
Software Architect / Software Engineer / Tech Lead
Last position:
Senior DevOps / Platform Engineer at Kaufland e-commerce / real.digital (ex hitmeister.de)
- Evolved the platform from bare-metal infrastructure with a monolithic PHP application to a hybrid Google Cloud architecture with Go microservices on Kubernetes
- Managed and scaled a production infrastructure with 300+ VMs and dozens of clusters, including MySQL, PostgreSQL, MongoDB, RabbitMQ, Redis and Elasticsearch clusters
- Evolved the platform from bare-metal infrastructure with a monolithic PHP application to a hybrid Google Cloud architecture with Go microservices on Kubernetes
- Managed and scaled a production infrastructure with 300+ VMs and dozens of clusters, including MySQL, PostgreSQL, MongoDB, RabbitMQ, Redis and Elasticsearch clusters
- Designed architecture, deployment, monitoring, performance analysis, and upgrades for all platform services using Terraform and Ansible
- Migrated observability systems from ELK and Prometheus to Datadog, managed with Terraform
- Introduced Jenkins CI/CD with SonarQube integration and automated tests to speed up feedback cycles
- Containerized the testing environment and implemented GitLab CI pipelines for Docker image builds, static code analysis, and infrastructure tests
- Performed zero-downtime migrations of MySQL and MongoDB clusters to Google Cloud
- Developed reusable Ansible roles for database clusters and automated data obfuscation for staging environments
- Decomposed monolithic databases and migrated to microservice architectures
- Built tools to detect and optimize slow queries in MySQL and MongoDB
- Conducted online schema migrations with pt-online-schema-change without downtime windows
- Developed internal Go applications for batch queries, GitLab-Jira integration, and MongoDB backup recovery
- Technologies: Debian, Ubuntu, Alpine, Go, Bash, Python, PHP, SQL, GitLab CI, Jenkins, Drone CI, MySQL, MongoDB, PostgreSQL, Redis, Elasticsearch, RabbitMQ, Kafka, Docker, Kubernetes, Nomad, Ansible, Terraform, Grafana, ELK, Prometheus, Datadog, Nagios, Zabbix, Nginx, HAProxy, Vault, Helm, SonarQube, Filebeat, Auditbeat, Google Cloud, AWS
- Designed architecture, deployment, monitoring, performance analysis, and upgrades for all platform services using Terraform and Ansible
- Migrated observability systems from ELK and Prometheus to Datadog, managed with Terraform
- Introduced Jenkins CI/CD with SonarQube integration and automated tests to speed up feedback cycles
- Containerized the testing environment and implemented GitLab CI pipelines for Docker image builds, static code analysis, and infrastructure tests
- Performed zero-downtime migrations of MySQL and MongoDB clusters to Google Cloud
- Developed reusable Ansible roles for database clusters and automated data obfuscation for staging environments
- Decomposed monolithic databases and migrated to microservice architectures
- Built tools to detect and optimize slow queries in MySQL and MongoDB
- Conducted online schema migrations with pt-online-schema-change without downtime windows
- Developed internal Go applications for batch queries, GitLab-Jira integration, and MongoDB backup recovery
- Technologies: Debian, Ubuntu, Alpine, Go, Bash, Python, PHP, SQL, GitLab CI, Jenkins, Drone CI, MySQL, MongoDB, PostgreSQL, Redis, Elasticsearch, RabbitMQ, Kafka, Docker, Kubernetes, Nomad, Ansible, Terraform, Grafana, ELK, Prometheus, Datadog, Nagios, Zabbix, Nginx, HAProxy, Vault, Helm, SonarQube, Filebeat, Auditbeat, Google Cloud, AWS
Mayuri Kolekar
Platform Engineer
Last position:
Platform Engineer at Madison Logic
- Designed and operated a GitOps-based Kubernetes platform, migrating services from AWS ECS to Amazon EKS.
- Built automated CI/CD pipelines for container build and deployment using GitLab CI, Helm, and Argo CD.
- Developed reusable Helm charts for Kubernetes resources (Ingress, Services, Secrets, HPA, ExternalDNS).
- Provisioned and managed EKS (Fargate and EC2) using Infrastructure as Code (Terraform / OpenTofu).
- Implemented OIDC-based authentication and authorization (Okta) for secure access to Kubernetes and Argo CD.
- Improved container security by migrating services to distroless images.
- Implemented logging, monitoring, and observability to ensure system reliability and performance.
- Automated cloud cost optimisation using Python (Boto3), achieving approximately 45% cost savings.
- Led migration of AWS infrastructure to IaC, reducing configuration drift and deployment issues.
- Produced technical documentation and operational runbooks, supporting internal engineering teams.
Mayuri Kolekar
Platform Engineer
Last position:
Platform Engineer at Madison Logic
- Designed and operated a GitOps-based Kubernetes platform, migrating services from AWS ECS to Amazon EKS.
- Built automated CI/CD pipelines for container build and deployment using GitLab CI, Helm, and Argo CD.
- Developed reusable Helm charts for Kubernetes resources (Ingress, Services, Secrets, HPA, ExternalDNS).
- Designed and operated a GitOps-based Kubernetes platform, migrating services from AWS ECS to Amazon EKS.
- Built automated CI/CD pipelines for container build and deployment using GitLab CI, Helm, and Argo CD.
- Developed reusable Helm charts for Kubernetes resources (Ingress, Services, Secrets, HPA, ExternalDNS).
- Provisioned and managed EKS (Fargate and EC2) using Infrastructure as Code (Terraform / OpenTofu).
- Implemented OIDC-based authentication and authorization (Okta) for secure access to Kubernetes and Argo CD.
- Improved container security by migrating services to distroless images.
- Implemented logging, monitoring, and observability to ensure system reliability and performance.
- Automated cloud cost optimisation using Python (Boto3), achieving approximately 45% cost savings.
- Led migration of AWS infrastructure to IaC, reducing configuration drift and deployment issues.
- Produced technical documentation and operational runbooks, supporting internal engineering teams.
- Provisioned and managed EKS (Fargate and EC2) using Infrastructure as Code (Terraform / OpenTofu).
- Implemented OIDC-based authentication and authorization (Okta) for secure access to Kubernetes and Argo CD.
- Improved container security by migrating services to distroless images.
- Implemented logging, monitoring, and observability to ensure system reliability and performance.
- Automated cloud cost optimisation using Python (Boto3), achieving approximately 45% cost savings.
- Led migration of AWS infrastructure to IaC, reducing configuration drift and deployment issues.
- Produced technical documentation and operational runbooks, supporting internal engineering teams.
Patrick Scheel
Senior Platform Engineer | Kubernetes | GitOps | Site Reliability Engineering
Last position:
Site Reliability / Platform Engineer – AIS Healthcare Platform at Labtastic Solutions UG (limited liability)
- Operated and stabilized Kubernetes platform
- Implemented a complete observability stack
- Set up GitOps deployment processes with ArgoCD
- Defined SLIs/SLOs and governance
- Conducted incident analysis and automated operations
Patrick Scheel
Senior Platform Engineer | Kubernetes | GitOps | Site Reliability Engineering
Last position:
Site Reliability / Platform Engineer – AIS Healthcare Platform at Labtastic Solutions UG (limited liability)
- Operated and stabilized Kubernetes platform
- Implemented a complete observability stack
- Set up GitOps deployment processes with ArgoCD
- Defined SLIs/SLOs and governance
- Conducted incident analysis and automated operations
- Operated and stabilized Kubernetes platform
- Implemented a complete observability stack
- Set up GitOps deployment processes with ArgoCD
- Defined SLIs/SLOs and governance
- Conducted incident analysis and automated operations
Osal Gotschiew
GCP Specialist - Platform Engineering & Architect
Last position:
GCP Specialist - Platform Engineering & Architect at Deutsche Glasfaser Holding
- Architectural Design of GCP Infrastructure Models
- Consultant for Strategic Migration Decisions
- Lead Engineer for Platform Automation
- Lead Engineer for Deployment of New Applications
Osal Gotschiew
GCP Specialist - Platform Engineering & Architect
Last position:
GCP Specialist - Platform Engineering & Architect at Deutsche Glasfaser Holding
- Architectural Design of GCP Infrastructure Models
- Consultant for Strategic Migration Decisions
- Lead Engineer for Platform Automation
- Lead Engineer for Deployment of New Applications
- Architectural Design of GCP Infrastructure Models
- Consultant for Strategic Migration Decisions
- Lead Engineer for Platform Automation
- Lead Engineer for Deployment of New Applications
Ilya Isakov
Data/Platform/Software Engineer/SRE
Last position:
Data/Platform/Software Engineer/SRE at IT Consulting
- Designed a platform based on IoT, Azure, Kubernetes, and Postgres for an existing application
- Migrated from "click-ops" and UI-defined CI/CD pipelines to infrastructure-as-code with Terraform, enabling complete redeployment of multiple environments
- Technologies: Terraform, OpenTofu, Azure, Azure DevOps, Kafka, IoT, Kubernetes, Grafana, Prometheus, GitOps, relational databases
Ilya Isakov
Data/Platform/Software Engineer/SRE
Last position:
Data/Platform/Software Engineer/SRE at IT Consulting
- Designed a platform based on IoT, Azure, Kubernetes, and Postgres for an existing application
- Migrated from "click-ops" and UI-defined CI/CD pipelines to infrastructure-as-code with Terraform, enabling complete
- Designed a platform based on IoT, Azure, Kubernetes, and Postgres for an existing application
- Migrated from "click-ops" and UI-defined CI/CD pipelines to infrastructure-as-code with Terraform, enabling complete redeployment of multiple environments
- Technologies: Terraform, OpenTofu, Azure, Azure DevOps, Kafka, IoT, Kubernetes, Grafana, Prometheus, GitOps, relational databases
redeployment of multiple environments
- Technologies: Terraform, OpenTofu, Azure, Azure DevOps, Kafka, IoT, Kubernetes, Grafana, Prometheus, GitOps, relational databases
Madhu Janjanam
Platform Developer II
Last position:
Platform Developer II at Salesforce
- Successfully completing certification requirements
- Trailhead
- Credential ID: 3483871
Madhu Janjanam
Platform Developer II
Last position:
Platform Developer II at Salesforce
- Successfully completing certification requirements
- Trailhead
- Credential ID: 3483871
- Successfully completing certification requirements
- Trailhead
- Credential ID: 3483871
Discover over 15,000 top freelancers
Platform Engineers statistics
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
2.3 years
Positions per freelancer
7
Top business areas
Information Technology, Operations, Product Development
Top industries
Information Technology, Automotive, Retail
Certification focus areas
Information Technology, Product Development, Operations
Bachelor's degree or higher
92%
Master's degree or higher
31%
Certifications per freelancer
4
Most common languages
English, German, Azerbaijani
Speak two or more languages
100%
Daily Rate Distribution
The chart shows how the daily rates of freelancers in this role are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Average rates for Platform Engineers & Seniority distribution
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Frequently Asked Questions
Want to learn more? Find helpful information about FRATCH
While a DevOps engineer focuses on bridging the gap between development and operations for specific applications, a platform engineer builds and maintains the shared infrastructure platform that serves multiple development teams. They treat the infrastructure as a product, creating self-service tools and workflows that allow other developers to deploy software independently.
A freelance platform specialist typically delivers fully automated infrastructure as code templates, secure CI/CD pipelines, and internal self-service portals. They also provide comprehensive documentation and conduct training sessions to ensure your permanent team can easily maintain the platform.
Yes, most freelance platform engineers work entirely remote, as cloud infrastructure and deployment pipelines can be managed securely from anywhere. However, some German enterprises prefer occasional on-site workshops, especially during the initial architecture phase or when dealing with highly sensitive on-premise infrastructure.
A professional cloud platform developer usually specializes in major cloud providers like AWS, Azure, or Google Cloud, combined with container orchestration tools like Kubernetes. They also utilize infrastructure management tools such as Terraform, Helm, and GitOps workflows to automate environments.
A qualified platform architect should be evaluated by their past success in reducing deployment times and improving developer friction. Look for experience in designing production-grade Kubernetes environments and check their understanding of security best practices, such as IAM and network segmentation.
Hiring a freelance platform engineering consultant in Germany allows you to access specialized cloud-native expertise immediately to bootstrap your platform. This avoids the lengthy hiring cycles of the German tech market and gives you the flexibility to scale down the project once the self-service infrastructure is fully operational.
While many international tech teams in Germany operate completely in English, some organizations, especially in the public sector or traditional manufacturing, require a German-speaking platform engineer for smoother collaboration. It is best to define these communication needs clearly before starting your search.
A skilled infrastructure platform engineer integrates security directly into the developer workflow through automated vulnerability scanning and policy enforcement. In European markets, they ensure the underlying platform architecture complies with strict regulations like GDPR and security frameworks such as ISO 27001.
The average hourly rate for Platform Engineers in Germany is 97 €, which corresponds to a daily rate of about 773 € based on an 8-hour working day.
Of the freelancers working as Platform Engineers in Germany, 92% hold at least a Bachelor's degree and 31% hold at least a Master's degree.
On average, freelancers working as Platform Engineers in Germany have 14 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers working as Platform Engineers in Germany are English (100%), German (93%), and Azerbaijani (7%).
The most common industries among freelancers working as Platform Engineers in Germany are Information Technology (100%), Automotive (33%), and Retail (33%).
The most common business areas among freelancers working as Platform Engineers in Germany are Information Technology (100%), Operations (73%), and Product Development (67%).
FRATCH Platform Engineers main locations
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a Free Demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
