Multi-Cloud Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Multi-Cloud
Tezcan Dilshener
Last position:
Solution Architect / Project Manager at German Football Association
- Overall responsibility for the project lifecycle from scope definition to completion
- Close collaboration with platform teams, IT leaders, and external service providers
- Application of SAFe principles and structured sprint work
- Creation of a migration roadmap with clear milestones
- Monitoring of the lifecycle: onboarding, repository migration, replication of permissions, and system tests
- Visualization of the architecture with PlantUML and Gliffy as well as documentation in Confluence
- Regular status reports and running knowledge transfer sessions
Thomas Hoefkens
Last position:
Senior MLOps, DevOps Engineer at Trianel Energy
- Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
- Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
- Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
- Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
- Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
- Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
- Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
- Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
- Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
- Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
- Integration of RESTHeart to create a REST API for MongoDB.
- Build an Angular frontend to simplify data queries and master data maintenance.
- Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
- Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).
Hardeep Bhutter
Last position:
Sr. Data Engineer at Charles Schwab Bank
- 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.
Tobias Nawa
Last position:
Enterprise & Solutions Architect
- Building an independent enterprise IT setup — cloud strategy, network, AWS landing zone, security requirements, contract negotiations.
- Migration of all applications; avoiding high contractual penalties for the client.
- Onboarding and coordination o...
Marc Esser
Last position:
Scrum Master for Agile Transformation and Team Development - DevOps & Cloud Adoption at IT Business Unit of Leading European OEM
- Guided a large-scale agile transformation, improving team agility, DevOps adoption, and cloud readiness.
- Supported DevOps & CI/CD practices to optimize cloud deployment strategies and reduce time-to-market.
- Led agile coaching initiatives to enhance cross-functional collaboration between IT and business teams.
- designed agile governance structures to align executive leadership with cloud and digital transformation goals.
- Technologies & Frameworks: Agile (Scrum, SAFe), DevOps, Cloud Adoption, IT Governance, CI/CD, Change Management
Alexandru Gunescu
Last position:
Head of Cloud Infrastructure at BP
- Migrated the Electric Vehicle Charging SaaS App of the EV Division from on-premises and Azure to AWS Cloud, resulting in a hybrid multi-cloud multi-tenant solution
- Developed a streaming data pipeline using AWS MSK for Apache Kafka and implemented an event-driven architecture to ingest and process near real-time data from OCPI-protocol IoT devices
- Implemented multi-tenant strategies including database schema isolation, bridge model for resource sharing, and tenant-based RBAC controls
- Provisioned Kubernetes clusters on AWS EKS with namespaces and RBAC for tenant isolation
- Led migration from on-premises and Azure to AWS using AWS DataSync, Snowball, and Database Migration Service
- Orchestrated collaboration across 5+ systems, vendors, service providers, and on-site teams
- Supported development and maintenance of IT strategy aligned with business requirements
- Managed €40 million infrastructure budget with AWS & Azure cost optimization, achieving 15% savings
- Led 50+ developers to implement advanced database procedures, increasing productivity by 20%
- Spearheaded multi-cloud, multi-tenant infrastructure migration for 30% faster processing times
- Negotiated vendor pricing to reduce payroll/benefits administration costs by 20%
- Developed a two-year infrastructure technology roadmap yielding 25% cost savings
- Tech stack: Kubernetes on AWS EKS, Docker, Kafka/AWS MSK, Terraform, AWS CDK, TypeScript, React, NextJS, Node.js, NestJS, Python, Aurora Serverless, RDS (MySQL, SQL Server), GitHub Actions, Azure DevOps, ArgoCD, AWS Lambda, API Gateway, AWS Security Hub, AWS Database Migration Service, AWS DataSync, AWS Organizations, AWS Control Tower, Odoo, Microsoft Navision, MS Dynamics
Discover over 15,000 top freelancers
Statistics of experts using Multi-Cloud
Aggregated from the professional profiles of matched freelancers.
Experience
23 years (Germany: 19 years)
Position duration
2 years
Positions per freelancer
12 (Germany: 14)
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Information Technology, Automotive, Transportation
Certification focus areas
Information Technology, Human Resources, Operations
Bachelor's degree or higher
100% (Germany: 87%)
Master's degree or higher
80% (Germany: 48%)
Doctorate
20% (Germany: 4%)
Certifications per freelancer
2 (Germany: 7)
Most common languages
English, German, Romanian
Speak two or more languages
83% (Germany: 98%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Munich 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.
Average rates of experts in Munich using Multi-Cloud
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.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Multi-cloud basics
Multi-cloud means using more than one cloud provider in the same landscape. Companies use it to spread workloads across AWS, Microsoft Azure, Google Cloud and other services without tying every system to a single vendor.
Where it fits
It shows up in application hosting, data platforms, backup and disaster recovery, analytics, and regulated systems. Strong multi-cloud work keeps identity, networking, security and deployment rules clear across each provider.
Typical deliverables
- Cloud landing zones and account structures
- Connectivity between clouds and on-prem systems
- Deployment pipelines and release standards
- Monitoring, logging and alerting across providers
- Cost and usage controls
Skills that matter
A good multi-cloud specialist understands architecture, infrastructure as code, networking, security and automation. They should know how services differ between providers and how to keep operations consistent when each cloud behaves differently.
When companies bring in freelance help
Teams usually need extra support when they are adding a second cloud, untangling vendor lock-in, or moving critical systems between environments. In Munich, this often comes up in manufacturing, mobility, finance and enterprise IT teams that need clear collaboration with both local and remote experts.
What strong experts do
They document decisions, define guardrails and keep the setup maintainable. They also test failover, review permissions, standardize deployment patterns and make sure teams can operate the landscape without guesswork.
Frequently asked questions
Quick answers to the questions that come up most around Multi-Cloud.
Multi-cloud is used to run workloads across more than one cloud provider, often to improve resilience, flexibility or vendor choice. Companies use it for application hosting, data services, backup and recovery, and regulated workloads that need clear control over where systems run.
Multi-cloud focuses on using several public cloud providers together. Hybrid cloud usually means combining public cloud with private infrastructure or on-prem systems. Many real setups use both, but the goals and operating models are not the same.
A multi-cloud setup often includes AWS, Microsoft Azure and Google Cloud. Some companies also add IBM Cloud, Oracle Cloud or smaller specialist services where a specific workload fits better. The exact mix depends on security, existing contracts and technical fit.
A strong Multi-Cloud specialist usually brings infrastructure as code, networking, identity and access control, security design and automation. Familiarity with Kubernetes, CI/CD pipelines, observability and cost management is also important because the work spans more than one provider.
The right multi-cloud profile depends on scope. A small migration or a proof of concept may only need focused support, while a production landscape with shared identity, networking and governance needs someone who has already solved similar problems end to end.
Many Multi-Cloud tasks can be handled remotely, especially architecture, automation and documentation. On-site time in Munich helps when stakeholders need workshop sessions, security reviews or coordination with local IT teams. A hybrid setup often works best.
Look for clear design choices, not just cloud tool names. A strong multi-cloud freelancer can explain trade-offs, show how they handled identity, networking and failover, and describe how they kept the setup manageable for the team after handover.
Bring a clear view of your current cloud landscape, target providers, security constraints and the systems that must stay available. For multi-cloud, good input includes network diagrams, access models, deployment paths and any pain points around cost, governance or portability.
The average hourly rate of freelancers in Munich, Germany who have used Multi-Cloud in their recent projects is 115 €, which corresponds to a daily rate of about 919 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Multi-Cloud in their recent projects, 100% hold at least a Bachelor's degree, 80% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Munich, Germany who have used Multi-Cloud in their recent projects have 23 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Munich, Germany who have used Multi-Cloud in their recent projects are English (100%), German (83%), and Romanian (33%).
The most common industries among freelancers in Munich, Germany who have used Multi-Cloud in their recent projects are Information Technology (100%), Automotive (67%), and Transportation (67%).
The most common business areas among freelancers in Munich, Germany who have used Multi-Cloud in their recent projects are Information Technology (100%), Business Intelligence (83%), and Project Management (83%).
Main locations of FRATCH Experts, who have recently used Multi-Cloud
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 
Frankfurt Request a free demo
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Philipp Thomaschewski
FRATCH CEO
