Apache Airflow Experts in Cologne
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Meet FRATCH Experts in Cologne, who have recently used Apache Airflow
Alexander B.
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
Fahad R.
Last position:
Data Science – Operations Optimization at Netto-marken
Project: Digitalization of Warehouse Processes | Building a Data Analytics Platform.
- Built a web-based workforce allocation system that digitized daily shift planning by matching worker expertise to operational zones, replacing manual coordination with a structured workflow adopted across the site, saving supervisors time on daily planning.
- Developed a real-time operational visibility dashboard giving supervisors a live view of task throughput and outstanding workload across warehouse zones throughout the day, helping reduce overtime and idle labour costs.
- Developed a slotting optimization solution to improve warehouse picking efficiency and reduce picking time per order, working directly with operations teams from concept through production deployment.
Technologies used: Python, Django, PostgreSQL, Pandas, NumPy, HTML, Java, JavaScript, Docker, Kubernetes, AWS, Power BI, GitHub Actions CI/CD, GitOps, Claude, OpenAI
Rainer L.
Last position:
Senior IT Consultant, Senior Software Architect, Senior Software Developer, Senior DevOps Engineer at Techniker Krankenkasse
Automation of the database major / minor releases for the TKeasy project
Concept for database major / minor release automation
As-is analysis
Evaluation of Redgate Flyway functionality
Concept creation
Products: Redgate Flyway, GitHub, Quest, Erwin Data Modeller, Oracle, Atlassian Jira, Atlassian Confluence
Skills: Docker, Continuous Delivery, Continuous Integration, Redgate Flyway, Major Releases, Minor Releases
Johannes W.
Last position:
Senior Data Engineer at Soorce GmbH
- Analysis of business requirements
- Integration of different data sources such as ERP systems, production systems, and external data sources
- Implementation of load processes and processing logic with MSSQL
- Data modeling and optimization of data models
- Setting up data quality management incl. data profiling with dynamic programming
- Support in designing and establishing data governance, especially in the areas of data quality management and data protection
- Support in developing BI solutions with Tableau to help decision-making processes
Emmanouil T.
Last position:
Senior Analytics Engineer at Trade Republic Bank GmbH
- Implementation of analytics and automation solutions for the Anti Financial Crime business unit
- Providing the infrastructure, including reusable data models and feature ingestion for production ML and rule based models in the areas of Account Take-Over and Card fraud detection, as well as Customer Risk Assessment
- Tools used: Snowflake, dbt, Looker, AWS, Python, Airflow, Metaflow
Pappu P.
Last position:
Senior Cloud Consultant (AWS Services and Consulting) at devoteam GmbH
- Developed automated ETL pipelines with AWS Glue and Athena to ensure consistent data quality and governance requirements
- Implemented validation, anonymization, and encryption measures for data in compliance with GDPR
- Optimized cloud costs by introducing FinOps practices and increased transparency for business units
- Monitored performance, performed root cause analyses, and ensured adherence to SLAs
- Supported data and solution architects in building scalable data models for ML and analytics scenarios
Discover over 15,000 top freelancers
Statistics of experts using Apache Airflow
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
1.3 years (Germany: 1.9 years)
Positions per freelancer
10 (Germany: 9)
Top business areas
Business Intelligence, Information Technology, Quality Assurance
Top industries
Education, Banking and Finance, Information Technology
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
100% (Germany: 99%)
Master's degree or higher
83% (Germany: 69%)
Certifications per freelancer
5 (Germany: 3)
Most common languages
German, English, Greek
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 Cologne 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 Cologne 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.
- Education (83%)
- Banking and Finance (67%)
- Information Technology (67%)
- Automotive (50%)
- Insurance (50%)
- Transportation (50%)
- Manufacturing (50%)
- Retail (50%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What it does
Apache Airflow is used to orchestrate data workflows, batch jobs, and cross-system dependencies. Teams use it to turn scattered scripts into clear DAGs with schedules, retries, alerts, and handoffs that are easy to follow.
Where it fits
- ETL and ELT pipelines
- Warehouse loads and data quality checks
- API syncs and file-based transfers
- ML training, feature refresh, and model scoring
It is a common choice when workflows need control, visibility, and repeatable execution instead of one-off cron jobs.
Core stack
Strong Airflow work touches Python, SQL, Docker, and a metadata database. Specialists also know executors, task isolation, connections, variables, secrets, and how to package code so DAGs stay clean and maintainable.
When companies hire help
Teams bring in freelance expertise when DAGs are growing fast, runs are failing without clear reasons, or orchestration needs to move from ad hoc scripts to a production setup. In Cologne, this often matters for analytics teams that work with local operations, logistics, media, or retail data and need clear handover to internal staff.
What strong specialists deliver
A good professional writes readable DAGs, sets sensible schedules, and avoids fragile task chains. They handle retries, sensors, branching, SLAs, and dependencies with care, then document how the workflow should be operated and extended.
Signs you need Airflow expertise
- Jobs overlap or miss their windows
- Failures are hard to trace
- New pipelines copy old patterns
- Deployment and environment setup are inconsistent
If the team is weighing Apache Airflow against cron, Prefect, or Dagster, a specialist can help choose the right fit and shape the workflow design before technical debt grows.
Frequently asked questions
Not sure where to start with Apache Airflow? These answers cover the essentials.
Apache Airflow is used to orchestrate workflows that must run in a defined order. It is a fit for ETL, ELT, data quality checks, API syncs, and scheduled jobs that depend on other tasks completing first.
Airflow is stronger than cron when workflows need dependencies, retries, logging, and visible task state. Compared with Prefect or Dagster, it is often chosen for mature scheduling and broad ecosystem support, while the final choice depends on how much orchestration control the project needs.
A strong Apache Airflow specialist usually brings Python, SQL, Docker, and solid understanding of task design. Experience with warehouses, APIs, secrets management, and deployment helps, because orchestration problems often sit between code, infrastructure, and data systems.
You do not always need a long profile, but you do need proof of real workflow delivery. Look for someone who has built DAGs that survive failures, handle backfills, and stay readable when the number of tasks grows.
Bring in Airflow help when pipelines are unstable, schedules are unclear, or a team needs to redesign orchestration without slowing delivery. Freelance support also makes sense when an internal team knows the data work but lacks time to clean up the workflow layer.
Yes, Apache Airflow work is often well suited to remote collaboration because most delivery happens in code, config, and runbooks. On-site time in Cologne can help during discovery, but ongoing DAG development and review usually work fine with shared access and clear process.
Judge Airflow quality by how the specialist explains dependencies, failure handling, and operational support. Strong work is readable, testable, and easy to operate, with sensible use of retries, sensors, alerts, and environment separation.
In Cologne, Apache Airflow projects often need smooth coordination with existing data stacks and clear communication with technical and non-technical stakeholders. Companies usually expect clean handover, predictable scheduling, and a workflow design that fits their teams, whether the work is remote or partly on-site.
The average hourly rate of freelancers in Cologne, Germany who have used Apache Airflow in their recent projects is 96 €, which corresponds to a daily rate of about 768 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used Apache Airflow in their recent projects, 100% hold at least a Bachelor's degree and 83% hold at least a Master's degree.
On average, freelancers in Cologne, Germany who have used Apache Airflow in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 1.3 years.
The most common languages among freelancers in Cologne, Germany who have used Apache Airflow in their recent projects are German (100%), English (100%), and Greek (17%).
The most common industries among freelancers in Cologne, Germany who have used Apache Airflow in their recent projects are Education (83%), Banking and Finance (67%), and Information Technology (67%).
The most common business areas among freelancers in Cologne, Germany who have used Apache Airflow in their recent projects are Business Intelligence (100%), Information Technology (100%), and Quality Assurance (83%).
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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