AWS Glue Expert in Munich
for reliable data pipelines, matched in minutes with vetted freelancersHire experts who design serverless ETL workflows, build searchable data lakes and connect AWS Glue with analytics services such as Amazon Athena and Amazon Redshift. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used AWS Glue
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Developed measures to improve management steering during a restructuring program (approx. 80 participants)
- Set up a PMO to ensure transparency, reporting and data-driven decisions
- Created an integration template to transfer team s...
Vitaliy R.
Last position:
DevOps GitOps (temp) at Signal Iduna
- Responsible for Openshift/Kubernetes on-prem administration and developer support.
- Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
- Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
- Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
- Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
- Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.
Hardeep B.
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.
Alexandre S.
Last position:
Cloud Engineer at Dectris AG
- Build a scalable multi-region backend service in AWS to serve remote desktop virtual machines for scientific analysis
- Stack: AWS, GitHub, Terraform, Python, Rust
- Built and defined the core infrastructure of the backend system
- Defined and coded the virtual machines provisioning supporting Ubuntu and Rocky Linux desktop setups
- Programmed the API service running in ECS to manage virtual machines and build custom Docker images for users
Jiri S.
Last position:
Quality Manager/Test Management at Noriba GmbH
- Test concept creation
- Creation of test processes
- Coordination of TC development: stress tests, functional tests, performance tests, high data rate tests, integration tests, etc.
- HW testing: FPGA, RF
- Test automation and regression tests
- Ensuring 24/7 operation of the test system
- Analysis & reporting
- Regular coordination of the test team, meetings with other stakeholders
- Communication and coordination with stakeholders and the project manager
Stephan S.
Last position:
Senior Data/ML Consultant & Technical Lead at Jolin.io
Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)
Maziyar K.
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
Thorsten G.
Last position:
Head of Real Estate Products | Technical Program Lead
- Program lead for a multi-year strategic partnership (~€9M device volume), reporting to the CTO (later CEO) and acting as primary executive interface to partner leadership.
- Owned cross-system delivery across firmware, hardware, cloud backend, manufacturing and partner engineering teams for two IoT products; improved system stability and observability to support reliable large-scale field operations (125k+ devices).
- Negotiated program roadmap and scope with partner leadership, aligning delivery commitments across hardware, firmware and cloud.
- Stabilized a strained executive partnership by restoring delivery reliability and establishing clear governance and scope boundaries.
- Delivered telemetry analysis system (Python, AWS) required by partner contract to detect malfunctioning heating systems and operational issues across deployed devices.
Max R.
Last position:
Cloud (AWS) | AI | DevOps | Data at Boehringer Ingelheim
- Architected and implemented an enterprise-grade AI Agent Platform leveraging Retrieval Augmented Generation (RAG) architecture to enhance clinical data insights.
- Established robust CI/CD pipelines for LLM applications using CDK and Jenkins, significantly reducing deployment times.
- Implemented comprehensive observability solutions that increased agent reliability across pharmaceutical environments.
- Designed scalable AI workflows with advanced orchestration that optimized context handling for enterprise data sources.
- Technologies: AI Agents (LangChain, LangGraph, Bedrock, Smolagents, Streamlit); LLM Operations (Tracing, Testing, Evaluation, LangSmith, LangFuse); Infrastructure-As-Code (AWS CDK, Terraform, Typescript, Jenkins); Vectors, Embeddings, RAG (OpenSearch, pgvector, PDF Extraction)
Discover over 15,000 top freelancers
Statistics of experts using AWS Glue
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 15 years)
Position duration
3 years (Germany: 2.1 years)
Positions per freelancer
10 (Germany: 9)
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Retail
Certification focus areas
Information Technology, Business Intelligence, Operations
Bachelor's degree or higher
89% (Germany: 93%)
Master's degree or higher
67% (Germany: 63%)
Doctorate
11% (Germany: 19%)
Certifications per freelancer
4
Most common languages
English, German, Spanish
Speak two or more languages
89% (Germany: 94%)
Based on our profile pool as of 19 Sep 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 AWS Glue
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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
AWS Glue experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (100%)
- Banking and Finance (67%)
- Retail (56%)
- Telecommunication (56%)
- Automotive (44%)
- Energy (44%)
- Manufacturing (33%)
- Pharmaceutical (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What AWS Glue does
AWS Glue is a serverless data integration service for discovering, preparing, transforming and loading data. It helps teams move information between sources such as Amazon S3, relational databases, streaming systems and data warehouses without managing server infrastructure. Its Data Catalog stores metadata that makes datasets easier to find and use.
Typical data workflows
AWS Glue specialists use the service to create dependable pipelines for analytics, reporting and machine learning. Common deliverables include:
- Crawlers that detect schemas and populate the Data Catalog
- ETL jobs with PySpark or Scala transformations
- Incremental loads, partitioning and data quality checks
- Workflows coordinated with triggers, schedules or event services
Ecosystem and tooling
Strong AWS Glue work connects several parts of the AWS data ecosystem. Professionals commonly work with Amazon S3, Lake Formation, Athena, Redshift, RDS, DynamoDB, Kinesis and Step Functions. They also use IAM, CloudWatch, AWS CloudFormation or Terraform to control access, deploy resources and monitor pipeline health.
When companies need specialists
Freelance expertise is useful when a team is modernising a warehouse, creating a data lake or replacing hand-built batch scripts. It also helps when pipelines fail under larger data volumes, permissions are unclear or multiple teams need consistent metadata. In Munich, specialists may support local teams on-site, remotely or in a hybrid model.
Skills that distinguish professionals
A capable AWS Glue professional understands more than job creation. They model schemas carefully, choose suitable partition keys, handle schema changes and design transformations that are easy to test and operate. They can also explain trade-offs between Glue jobs, Glue Studio, streaming approaches and alternative tools such as Amazon EMR or managed Airflow.
What quality looks like
Quality work produces repeatable pipelines with clear ownership, observable failures and controlled access to sensitive data. Look for practical experience with cost-aware Spark processing, retries, idempotent loads and deployment automation. The strongest specialists document lineage, test representative data and leave teams able to maintain the solution after handover.
Frequently asked questions
Questions about AWS Glue? Start with the answers below.
AWS Glue is mainly used to discover, catalog, transform and move data across AWS services and external sources. Companies use it for data lakes, warehouse loading, reporting pipelines and machine learning preparation.
AWS Glue provides managed, serverless data integration with less cluster administration. Amazon EMR offers broader control over Spark and other processing frameworks, so it can suit workloads that need deeper infrastructure or runtime customisation.
A strong AWS Glue specialist should understand PySpark, SQL, Python, data modelling and distributed processing. Knowledge of Amazon S3, Lake Formation, Athena, Redshift, IAM, CloudWatch and infrastructure as code is also valuable.
The right level depends on the assignment rather than a fixed time period. A simple catalog or ETL change may need focused AWS Glue experience, while a production lakehouse requires proven work with orchestration, security, monitoring, performance and recovery.
Yes. AWS Glue work is often well suited to remote collaboration because pipelines, infrastructure and documentation are managed digitally. For Munich-based teams, hybrid or on-site sessions can still help with data ownership, architecture decisions and stakeholder workshops.
Ask how the specialist would handle schema drift, late-arriving data, retries, partition design and failed jobs. A credible AWS Glue professional can explain decisions clearly, show how monitoring and tests work, and connect technical choices to operating costs and business requirements.
AWS Glue supports streaming ETL scenarios and can work with services such as Amazon Kinesis and Kafka. It is a good fit when teams need managed streaming transformations, but continuously low-latency workloads may call for a more specialised streaming architecture.
Freelancers working with AWS Glue should be comfortable discussing data residency, access controls, audit needs and documentation with German teams. Clear English is often essential in international projects, while German can support closer collaboration with local stakeholders.
The average hourly rate of freelancers in Munich, Germany who have used AWS Glue in their recent projects is 116 €, which corresponds to a daily rate of about 930 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used AWS Glue in their recent projects, 89% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers in Munich, Germany who have used AWS Glue in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Munich, Germany who have used AWS Glue in their recent projects are English (100%), German (89%), and Spanish (33%).
The most common industries among freelancers in Munich, Germany who have used AWS Glue in their recent projects are Information Technology (100%), Banking and Finance (67%), and Retail (56%).
The most common business areas among freelancers in Munich, Germany who have used AWS Glue in their recent projects are Information Technology (100%), Product Development (89%), and Project Management (78%).
Main locations of FRATCH Experts, who have recently used AWS Glue
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.
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Philipp Thomaschewski
FRATCH CEO
