Apache Airflow Expert in Nuremberg
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Meet FRATCH Experts in Nuremberg, who have recently used Apache Airflow
Partha N.
Last position:
AI Software Developer at Fraunhofer IIS
- Built a custom AI chatbot for an e-commerce client using GPT-4 and LangChain with RAG, reducing customer support ticket volume by 45% and improving response accuracy to 92%.
- Designed and deployed an intelligent document processing system using LlamaIndex, Pinecone, and FastAPI for a FinTech startup, enabling semantic search across 100K+ financial documents.
- Developed multi-agent AI workflows using CrewAI and LangGraph for a marketing agency, automating lead research, content generation, and outreach — saving 20+ hours/week of manual work.
- Created AI-powered automation pipelines using n8n, Make, and Zapier integrated with CRMs (GoHighLevel, HubSpot), reducing manual data entry by 80% for a real estate firm.
- Delivered prompt engineering and LLM fine-tuning consulting for multiple clients, optimizing AI model outputs for customer support, content creation, and data extraction use cases.
- Built production-ready REST APIs with Python and FastAPI to serve AI models on AWS and GCP, handling 10K+ daily requests with 99.9% uptime.
Arun Sai T.
Last position:
AI-Backend Developer Intern at Calvergy UA
- Integrated complex AI-based energy system models into the frontend framework, enabling the visualization of insights for 6+ key clients and maximizing energy utilization.
- Maximized energy efficiency and utilization by architecting the seamless data flow between AI models and the user interface for rapid, actionable reporting.
Elnazossadat H.
Last position:
Data Analyst at Siemens Healthineers
- Developed KPI dashboards using Power BI and DAX for 4+ business units, improving reporting transparency and strategic decision support.
- Migrated enterprise finance data views into dbt models, implementing modular SQL transformations, version-controlled data pipelines, and automated documentation to create a scalable analytics layer.
- Built dimensional data models in Snowflake for enterprise finance data, enabling scalable forecasting and supporting executive decision-making.
- Designed end-to-end ETL/ELT pipelines using Snowflake and SAP HANA, integrating data from 3+ enterprise systems.
- Automated monthly reporting workflows using SQL and Power BI, delivering strong business impact by reducing manual effort by 80%.
- Collaborated with finance stakeholders to translate business requirements into analytical data models, supporting strategic decision-making cycles.
- Delivered ad-hoc financial reports using Power BI, reducing turnaround time by 60%.
- Implemented data validation logic in SQL, resolving 95% of recurring data quality issues.
Pawan S.
Last position:
CAPTCHA Recognition using CRNN
- Built a CRNN model with VGG16 and BiLSTM backbone for text-based CAPTCHA recognition
- Achieved 9.37% character error rate and 68.36% sequence accuracy on validation data
- Expanded data augmentation pipeline with distortions, noise injection, and clutter to improve robustness
- Conducted detailed error analysis on confusable characters (O, Q, D) and proposed error-specific augmentation
- Tech Stack: Python, TensorFlow/Keras, OpenCV, NumPy, Matplotlib
Uddipan B.
Last position:
Research Team Member at Munich Music Labs, TUM
- Focused on exploring the intersection of Music and AI.
Vasuraj B.
Last position:
Cloud Data Analyst at Bhatia Reply
- Analyzed 50K+ customer records using SQL and Python in a cloud services firm, identifying trends
- Designed interactive Tableau dashboards for sales and marketing stakeholders, reducing report
- Developed ARIMA and AutoARIMA time series models to forecast AWS resource utilization, cutting
- Automated ETL pipelines with Python, improving workflow efficiency by 20% for scalable data
- Collaborated with DevOps teams to deploy 3 machine learning models in production using Docker
Guino N.
Last position:
Senior Data Engineer at Infomotion
- Built a data analytics platform for Karl Storz
- Developed all ETL processes in a generic way
- Prepared and supplied data in Databricks Delta tables for use in Databricks Machine Learning
- Technologies & Tools: Azure Data Factory, CI/CD pipeline with GitHub DevOps, Python, Azure Databricks (Unity Catalog), T-SQL
Discover over 15,000 top freelancers
Statistics of experts using Apache Airflow
Aggregated from the professional profiles of matched freelancers.
Experience
10 years (Germany: 14 years)
Position duration
2.2 years (Germany: 1.9 years)
Positions per freelancer
6 (Germany: 9)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Research and Development, Business Intelligence
Bachelor's degree or higher
100% (Germany: 99%)
Master's degree or higher
71% (Germany: 69%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, Hindi
Speak two or more languages
100% (Germany: 97%)
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 Nuremberg 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 Nuremberg using Apache Airflow
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.
Apache Airflow 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 (71%)
- Automotive (57%)
- Healthcare (43%)
- Retail (43%)
- Education (29%)
- Energy (29%)
- Manufacturing (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Orchestration
Apache Airflow is an open-source platform for authoring, scheduling and monitoring workflows. Teams define processes as directed acyclic graphs, or DAGs, so dependencies, retries and execution states remain visible. It is built for batch-oriented data movement and recurring operational processes rather than continuous event streaming.
Typical workflows
Companies use Airflow to coordinate data engineering and analytics work across many systems.
- Load data from applications, warehouses and APIs
- Transform datasets for reporting and machine learning
- Schedule quality checks, exports and regulatory processes
- Trigger jobs across cloud and on-premise environments
Ecosystem
Airflow connects with databases, object storage, cloud platforms and processing engines through providers and operators. Strong specialists work with Python, SQL, containers and deployment tooling, while understanding secrets management, logging, alerting and access control. They also know how to keep DAGs modular, testable and easy to operate.
When to hire
Freelance expertise helps when pipelines have become difficult to monitor, schedules are unreliable or a team needs to move from scripts to managed orchestration. Specialists can design a clear DAG structure, migrate existing jobs, establish deployment workflows and document operational ownership. In Nuremberg, they may support regional data, manufacturing, logistics or software teams remotely or alongside local staff.
Reliable delivery
A capable Airflow professional treats orchestration as production software. They define idempotent tasks, sensible dependencies and failure handling instead of hiding problems in retries. They also separate configuration from code, protect credentials, control resource use and make alerts useful to the people responsible for the workflow.
Project fit
The right specialist can review an existing environment or deliver a focused implementation. Useful work may include provider selection, DAG refactoring, scheduler tuning, observability and migration to a managed Airflow service. Clear communication matters when remote collaboration spans Nuremberg and other locations, particularly when teams need shared documentation and dependable handovers.
Frequently asked questions
Quick answers to the questions that come up most around Apache Airflow.
Apache Airflow is used to schedule and monitor workflows made up of dependent tasks. Companies commonly use it for data ingestion, transformations, warehouse loads, quality checks, reporting and operational automation.
Apache Airflow has a mature ecosystem, a broad provider catalogue and a strong model for scheduled batch workflows. Prefect and Dagster can offer different approaches to flow authoring, local development and asset management, so the best choice depends on team preferences, workload patterns and operating skills.
A strong Apache Airflow specialist usually brings Python, SQL, data warehouse knowledge and experience with cloud storage or processing services. Docker, Kubernetes, Terraform, CI/CD, observability and secrets management are also valuable when Airflow must run reliably in production.
Apache Airflow work can range from reviewing a few critical DAGs to designing an organisation-wide orchestration setup. The specialist should have relevant experience with the project’s data sources, deployment model, security needs and operational ownership rather than only having created sample workflows.
Ask how the Apache Airflow specialist handles retries, backfills, idempotency, testing, dependency design and alerting. A quality professional can explain trade-offs clearly, show how failures are investigated and produce DAGs that remain understandable as the workload grows.
Yes, Apache Airflow projects are often suitable for remote collaboration because DAGs, infrastructure and documentation can be reviewed digitally. Teams in Nuremberg should agree on communication routines, repository practices, access controls and any need for occasional on-site workshops.
An Apache Airflow specialist may add value on site when workflows depend on local systems, complex stakeholder processes or a shared data platform. Remote delivery can still work well when access, ownership and technical documentation are ready, with German or English communication agreed in advance.
Apache Airflow is primarily designed for scheduled and dependency-driven workflows, not continuous event processing. It can trigger or coordinate streaming components, but systems such as Kafka and dedicated stream-processing tools are usually better suited to low-latency event handling.
The average hourly rate of freelancers in Nuremberg, Germany who have used Apache Airflow in their recent projects is 75 €, which corresponds to a daily rate of about 601 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Apache Airflow in their recent projects, 100% hold at least a Bachelor's degree and 71% hold at least a Master's degree.
On average, freelancers in Nuremberg, Germany who have used Apache Airflow in their recent projects have 10 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Nuremberg, Germany who have used Apache Airflow in their recent projects are German (100%), English (100%), and Hindi (29%).
The most common industries among freelancers in Nuremberg, Germany who have used Apache Airflow in their recent projects are Information Technology (100%), Banking and Finance (71%), and Automotive (57%).
The most common business areas among freelancers in Nuremberg, Germany who have used Apache Airflow in their recent projects are Information Technology (100%), Business Intelligence (86%), and Product Development (86%).
Main locations of FRATCH Experts, who have recently used Apache Airflow
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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Cologne 
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