Azure Blob Storage Experts in Munich
in minutes with vetted freelancers from over 15,000 CVs and AI precision.Hire experts who design blob containers, set access tiers and lifecycle rules, and connect Azure Blob Storage to apps, data pipelines, and backup workflows. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Azure Blob Storage
Michael Nelz
Last position:
Senior ML Engineer, AI Engineer at Lanxess AG
- Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
- Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
- Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.
Serge Kalinin
Last position:
MLOps (machine learning operations) at REWE Digital GmbH
- It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
- GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
- Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
- CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
Stefan Wimmer
Last position:
Architect/Software Developer at Global Logistics Support GmbH
Task
- Further development of a new ERP system with Blazor
- Creation of e-invoices in the XRechnung and ZUGFeRD formats
- UI/UX design Client-server system
- Windows 11 Technology
- Microsoft .NET 9, Git, Azure DevOps, ASP.NET, MSSQL, Blazor Programming languages
- C#, MVVM Development tools
- Microsoft Visual Studio .NET 2022 Database
- MSSQL Industry
- Other
Maziyar Khorrami
Last position:
Data Engineer at MSD Germany
- Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
- Performance Optimization of Data Ingestion of ETL Pipeline
- Development of Data Validation using Great Expectations
- Leading of the data migration for two sources exchanges
- Data Modeling in AWS Redshift
MLOps
- Model inference implementation by mlflow and AWS SageMaker
- Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
- Implementatino of Model Registry and artifactory using mlflow
- Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
- Feature importance using mlflow
Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy
Mohamed Saleh
Last position:
Machine Learning Engineer (Part Time) at E.ON Digital Technology
- Designed and implemented an advanced, agentic RAG pipeline using LangChain and LangGraph for structured data extraction from PDFs, utilizing tools, state management, and OpenAI LLMs (GPT-4) to improve accuracy and handle complex document structures.
- Developed a Google AI agent for extraction of structured information from PDF documents and deployed the agent on Vertex AI.
- Architected data pipelines using Azure Data Factory and Databricks to ingest data from Azure Blob Storage, process it with PySpark, and load it into Azure SQL Database via Linked Services.
- Containerized AI agents and services using Docker for consistent local development and deployment.
- Utilized PySpark and Dask for database querying in coordination with Azure Blob Storage and Document Storage.
- Created a ReAct agent that extracts structured data from PDF documents using tools and integrating Azure Document Intelligence.
- Contributed to the CPO invoices validation check project using Databricks to find existing CDRs and calculate total valid costs.
- Developed a conversational AI agent (chatbot) with a FastAPI backend, integrating RAG for precise tariff extraction and deployed the service using Azure Container Apps.
- Tools used: Azure, Azure OpenAI, Azure Document Intelligence, Azure Blob Storage, Google ADK, Google Cloud, Vertex AI, Gemini, Databricks, LangChain, LlamaIndex Ollama, Docker, PySpark, Azure SQL, Azure Data Factory, Azure AI Agent, Microsoft SQL Server
Satish Kore
Last position:
Sustainability Intern at Forschungszentrum Jülich GmbH
- Developed energy estimation models to estimate electric charging and hydrogen refueling requirements at charging and refueling stations for logistics trucks in Germany.
- Estimated future freight traffic demand for Germany using an in-house transport demand model.
- Designed a network of electric charging and hydrogen refueling stations based on transport model results, supporting data-driven infrastructure planning.
Discover over 15,000 top freelancers
Statistics of experts using Azure Blob Storage
Aggregated from the professional profiles of matched freelancers.
Experience
13 years
Position duration
1.2 years
Positions per freelancer
14
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Insurance, Education
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100%
Master's degree or higher
100%
Doctorate
20%
Certifications per freelancer
3
Most common languages
German, English, Arabic
Speak two or more languages
100%
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 Azure Blob Storage
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
Storage basics
Azure Blob Storage is Microsoft’s object storage for unstructured data. It stores files, images, logs, backups, and large datasets in containers. Teams use Blob Storage when they need durable storage that is easy to access from apps, services, and analytics jobs.
Common use cases
- Static website content and media files
- Application logs, exports, and audit archives
- Backup, restore, and disaster recovery data
- Data lake landing zones for batch processing
- Shared file exchange between services and teams
Ecosystem fit
Blob Storage works with Azure Storage, Azure Active Directory, SAS tokens, lifecycle management, and tiering for hot, cool, and archive data. It often sits next to Azure Functions, Logic Apps, Data Factory, Synapse, and Kubernetes workloads that need persistent object storage.
What strong specialists do
Strong professionals know how to choose the right access model, structure containers and prefixes, and control cost without hurting retrieval time. They handle encryption, replication, immutability, versioning, and retention policies with care. They also write clear runbooks for backup, restore, and access troubleshooting.
When to bring one in
Bring in freelance expertise when storage grows messy, costs rise, or access rules become hard to manage. Companies in Munich often need help during cloud migrations, analytics projects, and platform rebuilds where teams want a clean Azure Storage design and reliable operations across English-speaking and local stakeholders.
Signs you need help
- Data is scattered across many containers or accounts
- Uploads, downloads, or signed access links are failing
- Lifecycle rules and archive tiers are not set up well
- Security, identity, or encryption settings need review
- Backup and restore steps are unclear or untested
Frequently asked questions
Curious about Azure Blob Storage? Here are the answers that come up again and again.
Azure Blob Storage is used for unstructured data such as documents, media, logs, exports, backups, and analytical input files. It is a common choice when teams need object storage that is durable, easy to automate, and simple to connect to Azure services.
Blob Storage is better for large files and objects that do not need relational queries or shared file-system semantics. Azure Files is closer to a traditional file share, while SQL databases are for structured records, transactions, and joins. The right choice depends on access pattern, not just where the data lives.
A strong Azure Blob Storage specialist usually knows access keys, SAS, managed identities, containers, lifecycle rules, replication, and encryption. Familiarity with Azure CLI, PowerShell, Terraform, and SDKs in .NET, Java, Python, or JavaScript is often useful when storage has to be automated.
Azure Blob Storage projects vary a lot. A simple upload-and-download setup may need only a focused specialist, while migration, governance, and disaster recovery work usually need someone who has handled security, cost control, and operational edge cases before.
Azure Blob Storage work is usually easy to do remotely because most tasks involve configuration, code, and review rather than physical infrastructure. Onsite time can still help at the start of a migration or workshop, especially in Munich when teams want to align storage patterns, access policies, and ownership quickly.
A good Blob Storage professional explains trade-offs clearly and does not oversimplify storage design. Look for clean naming, access control that follows least privilege, thoughtful lifecycle policies, tested restore procedures, and an approach that keeps both security and cost under control.
Azure Blob Storage is one service within Azure Storage, focused on object storage. Azure Data Lake Storage Gen2 builds on blob capabilities and adds a hierarchical namespace for analytics-style workloads, so the right specialist should know where those boundaries matter.
Azure Blob Storage migration work often includes mapping buckets or shares to containers, moving data safely, updating app connection strings, and checking permissions after the cutover. It can also involve setting tiers, policies, and backup rules so the new setup behaves well from day one.
The average hourly rate of freelancers in Munich, Germany who have used Azure Blob Storage in their recent projects is 87 €, which corresponds to a daily rate of about 697 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Azure Blob Storage in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Munich, Germany who have used Azure Blob Storage in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 1.2 years.
The most common languages among freelancers in Munich, Germany who have used Azure Blob Storage in their recent projects are German (100%), English (100%), and Arabic (17%).
The most common industries among freelancers in Munich, Germany who have used Azure Blob Storage in their recent projects are Information Technology (83%), Insurance (67%), and Education (50%).
The most common business areas among freelancers in Munich, Germany who have used Azure Blob Storage in their recent projects are Information Technology (100%), Business Intelligence (83%), and Product Development (83%).
Main locations of FRATCH Experts, who have recently used Azure Blob Storage
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.
Countries:
Berlin Hamburg 
Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
