Azure Synapse Analytics Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Azure Synapse Analytics
Manikanta Rangaswamy
Last position:
Data Engineer at Insurance client
- Design, development, and maintenance of end-to-end ETL pipelines for scalable and reliable data integration
- Support in data quality checks, testing, and migrations
- Development and maintenance of dbt models for structured, modular, and reusable data transformations
- Use of AI-driven development to improve ETL job creation and code quality.
- Development of CI/CD for automated deployment.
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.
Nima Nooshi
Last position:
Co founding LLM Engineer at LLM Ventures
- Co-founded an AI venture focused on building production-grade LLM applications and agentic systems
- Designed and implemented multi-agent AI workflows for financial and trading applications
- Developed LLM-powered copilot architectures for portfolio analysis, trade management, and personalized user coaching
- Built on-device and edge-deployed inference applications, optimizing models for low latency, privacy, and resource-constrained environments
- Led system architecture decisions across model selection, orchestration, state management, and deployment
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
Stefan Corsten
Last position:
SSIS Development at Stadtsparkasse München
- Replacement of a Java application and the Oracle DB for loading the internal WerWasWo system using SSIS.
- Development of SSIS packages to load text files into the database (SQL Server)
- Development of a database project for deployment on various servers
- Creation of queries to monitor the loading runs
- Development of a PowerShell script to automate the deployment of the SSDT projects.
- Oracle, SQL Developer, Microsoft SQL Server 2022 on-premises, SQL Server Management Studio v21, Visual Studio 2022, SSIS, SSDT, PowerShell.
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 Synapse Analytics
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
1.8 years (Germany: 2 years)
Positions per freelancer
14 (Germany: 12)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Banking and Finance, Information Technology, Professional Services
Certification focus areas
Information Technology, Business Intelligence
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
80% (Germany: 60%)
Doctorate
20% (Germany: 12%)
Certifications per freelancer
3 (Germany: 5)
Most common languages
English, German, Persian
Speak two or more languages
83% (Germany: 97%)
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 Synapse Analytics
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
What it covers
Azure Synapse Analytics brings data integration, SQL analytics, Spark processing, and reporting into one environment. Companies use it to combine raw data from many sources, shape it for analysis, and serve it to business teams in a controlled way. It is often discussed as Synapse Analytics or Azure Synapse.
Common use cases
- Build data pipelines with Synapse Pipelines
- Run ad hoc SQL over curated data
- Process large datasets with Spark
- Prepare warehouse layers for BI tools
- Connect data lake, lakehouse, and reporting flows
Tooling and ecosystem
Strong professionals know the Azure pieces around it, not just the Synapse workspace. That often includes Microsoft Entra ID, Azure Data Lake Storage, Power BI, Azure Monitor, and source systems such as SQL databases, APIs, and event streams. They also understand the older Azure SQL Data Warehouse background that still appears in real projects.
When companies bring in help
Teams usually look for freelance expertise when a warehouse needs redesign, pipelines fail, costs rise, or reporting becomes slow and hard to trust. In Munich, this often comes up in analytics work for manufacturing, mobility, insurance, and enterprise IT, where clean handover and clear documentation matter. Remote delivery is common, but on-site sessions help when data ownership or reporting needs are still unclear.
What strong specialists do
Good experts keep models simple, separate raw and curated layers, and tune SQL and Spark jobs for predictable runs. They write clear deployment steps, monitor pipeline health, and avoid hidden coupling between storage, transformation, and reporting. They also know when Synapse is the right fit and when a different Azure analytics setup is cleaner.
Skills to look for
A reliable specialist understands T-SQL, Spark notebooks, ETL/ELT design, security, and Azure governance. They should be able to work with business analysts, data owners, and BI teams without turning every change into a long technical debate. For Munich projects, clear English is often enough, while German can help in workshops and stakeholder reviews.
Frequently asked questions
Not sure where to start with Azure Synapse Analytics? These answers cover the essentials.
Azure Synapse Analytics is used to bring together data ingestion, transformation, SQL analytics, and Spark-based processing in one place. Companies use it for data warehouse work, lake access, and reporting flows that need tight control over data movement. It is a strong fit when several Azure services must work together.
Synapse Analytics sits between a classic warehouse and a broader analytics workspace. Compared with Databricks, it is often chosen when SQL warehousing and integrated pipeline management matter more than notebook-heavy data science. Compared with a traditional warehouse, it gives more room to work with data lakes and Spark.
A solid Azure Synapse Analytics specialist should know T-SQL, Spark, data modeling, pipeline orchestration, and Azure security basics. Experience with Power BI, Azure Data Lake Storage, and source-system integration is also valuable. The best specialists can move between technical design and business reporting needs.
The right level depends on whether you need a small pipeline fix, a warehouse redesign, or a full analytics setup. Azure Synapse work often needs someone who has already handled permissions, workspace structure, performance tuning, and deployment flow. If the project touches many source systems, choose a specialist who has delivered end-to-end work before.
Most Azure Synapse Analytics work can be done remotely because the main tasks are design, coding, testing, and review. On-site time in Munich helps when source systems, reporting needs, or governance rules need close discussion with local teams. A hybrid setup is common for workshops and project kickoffs.
Look for clear pipeline design, readable SQL, sensible Spark usage, and strong documentation. A good Synapse Analytics expert explains trade-offs, not just syntax, and can describe how they handle security, retries, and data quality checks. Ask for examples of production work, not only demos.
Yes. Many people still use Azure SQL Data Warehouse as an old name when they mean the warehouse side of Azure Synapse Analytics. A specialist should understand both the current Synapse setup and the older naming, because many real projects and internal documents still use the former term.
Ask which parts of the stack they have actually delivered: ingestion, transformation, SQL serving, Spark processing, or BI integration. With Azure Synapse Analytics, you want someone who can explain how they would structure the workspace, protect access, and keep the solution maintainable. Clear answers here are a strong sign of practical experience.
The average hourly rate of freelancers in Munich, Germany who have used Azure Synapse Analytics in their recent projects is 94 €, which corresponds to a daily rate of about 752 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Azure Synapse Analytics 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 Azure Synapse Analytics in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Munich, Germany who have used Azure Synapse Analytics in their recent projects are English (100%), German (83%), and Persian (17%).
The most common industries among freelancers in Munich, Germany who have used Azure Synapse Analytics in their recent projects are Banking and Finance (83%), Information Technology (67%), and Professional Services (50%).
The most common business areas among freelancers in Munich, Germany who have used Azure Synapse Analytics in their recent projects are Information Technology (100%), Business Intelligence (83%), and Product Development (50%).
Main locations of FRATCH Experts, who have recently used Azure Synapse Analytics
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 
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