Apache Airflow Experts in Austria
matched in minutes with vetted, available freelancers and the power of AIHire experts who orchestrate reliable data workflows, connect cloud services and operate production-grade DAGs with Apache Airflow. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your technical needs.
Meet FRATCH Experts in Austria, who have recently used Apache Airflow
Karl F.
Last position:
Managing Director at ONECEPT GmbH
Manuel P.
Last position:
AI Engineer at Misumi Europe GmbH & Motius GmbH
- Designed and built a next-generation NLP platform to accelerate sales-driven customer service through intelligent request analysis and routing, reducing average customer query response time by 30%.
- Architected a hybrid NLP system combining Large Language Models (LLMs) with traditional NLP pipelines for robust, explainable results.
- Developed request classification and routing mechanisms to accelerate customer support teams in handling customer queries faster and more accurately.
- Optimized LLM based data extraction and classification with context engineering.
- Integrated the platform into customer service processes, reducing response times and enhancing workforce efficiency.
Stefan D.
Last position:
BI Consultant in Controlling at Reutter GmbH
- Extraction, transformation, and cleansing of data from Microsoft Dynamics AX
- Creation of sales reports in Power BI
- Training employees in business intelligence
- Technologies: Power BI, SQL, SQL Server Integration Services (SSIS)
Stefania D.
Last position:
Data Engineer at Storebox
Tech: AWS (Glue, Lambda, Redshift), Airflow, PostgreSQL, Python, PySpark, Metabase, Power BI
Delivered: Analytics-Ready Data Models • Legacy SQL to Cloud ETL Migration • Dynamic Pricing Engine
- Owned and evolved the company data warehouse end-to-end — from ingestion to transformation to analytics-ready dimensional data models on AWS Redshift.
- Collaborated with Analysts, Data Scientists, and business stakeholders to deliver scalable dimensional data models that enable self-serve analytics and streamline dashboarding in Metabase and Power BI.
- Architected end-to-end ETL/ELT pipelines on AWS (Glue, Lambda, Redshift) using Python and PySpark, orchestrated with Apache Airflow (MWAA) for reliability and observability.
- Defined and enforced data quality standards and governance practices across pipelines and the core data layer.
- Led migration of legacy SQL infrastructure into scalable AWS Glue pipelines with distributed PySpark processing, eliminating bottlenecks and reducing downtime.
- Developed a dynamic pricing engine applying automated promotional discounts based on occupancy rates, competitor pricing, and location performance tiers.
- Designed schema mappings to ingest MongoDB data into structured relational systems (Redshift/PostgreSQL).
Marcel S.
Last position:
Senior AI Engineer - Python at Insurance Company
Project Tech Stack: Python, AWS, Azure, FastAPI, openai, pandas, unittest/pymock
Achievements:
- Engineered automated data extraction pipelines to transform complex Excel datasets into structured formats via LLM-driven workflows.
- Architected a generative slide-deck engine that translates natural language prompts into formatted presentation assets.
- Integrated advanced LLM capabilities with the OpenAI Response API, implementing sophisticated tool-calling and structured output logic.
- Developed and containerized scalable backend microservice using FastAPI, Docker, and OpenShift to host and serve agentic skills.
Kevin L.
Last position:
Data Consultant at VBV Pension and Provident Fund Austria
Development of a structured framework and comprehensive guidelines for documenting business and audit processes in a regulated financial environment. Support for the standardization of process documentation to improve transparency, consistency, and traceability across all operational workflows. Contribution to defining documentation standards, templates, and governance principles for internal process management and audit readiness.
Bernhard K.
Last position:
AI Consultant at Bitpanda
- Advising on AI strategy and implementation for one of Europe's leading digital asset platforms
- Helping teams integrate agentic AI workflows, optimize developer productivity through AI-assisted tooling, and evaluate emerging AI technologies for fintech applications
Discover over 15,000 top freelancers
Statistics of experts using Apache Airflow
Aggregated from the professional profiles of matched freelancers.
Experience
13 years
Position duration
1.5 years
Positions per freelancer
12
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Banking and Finance, Information Technology, Education
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100%
Master's degree or higher
83%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
100%
Based on our profile pool as of 16 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Austria are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Austria 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 16 Oct 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.
- Banking and Finance (71%)
- Information Technology (71%)
- Education (57%)
- Media and Entertainment (57%)
- Healthcare (43%)
- Manufacturing (43%)
- Retail (43%)
- Energy (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Workflow orchestration
Apache Airflow is an open-source platform for authoring, scheduling and monitoring data workflows. Teams define pipelines as Python-based directed acyclic graphs, or DAGs, and use dependencies to control how tasks run. It is built for workflows that need visibility, retries, alerts and clear operational ownership.
Data pipeline work
Airflow specialists use it to coordinate batch processing, analytics preparation, machine learning workflows and recurring business operations. A pipeline can extract data from operational systems, transform it with SQL or Spark, load it into a warehouse and trigger downstream reporting. Airflow manages the sequence while the processing systems perform the heavy work.
- Build DAGs for ingestion, transformation and data quality checks
- Schedule warehouse loads and model refreshes
- Coordinate machine learning training and deployment steps
- Add retries, alerts, backfills and operational controls
Ecosystem and tooling
Strong Apache Airflow work spans Python, SQL, cloud storage, data warehouses and container platforms. Common integrations include Amazon Web Services, Google Cloud, Microsoft Azure, Kubernetes, Apache Spark, dbt and provider packages. Professionals also work with metadata databases, executors, secrets management, CI/CD and observability tools.
When expertise matters
Companies often bring in freelance specialists when an existing orchestration setup has become difficult to maintain or a new data platform must go live quickly. They can review DAG design, improve scheduling, migrate from legacy scripts or establish deployment standards. In Austria, remote collaboration can suit distributed data teams, while on-site work may help with workshops, access controls or complex operational handovers.
- Replace fragile cron jobs with observable workflows
- Prepare Airflow for reliable production operations
- Tune concurrency, queues, retries and resource usage
- Establish testing, release and incident procedures
Quality signals
A capable professional separates orchestration logic from business transformations and keeps DAGs readable, modular and idempotent. They understand scheduling intervals, time zones, catchup behavior, task mapping, sensors and backfills rather than treating Airflow as a simple cron replacement. They also document dependencies and design for failure, recovery and safe reruns.
Selecting the right specialist
Ask for examples of production workflows similar to yours and discuss how failures, schema changes and late-arriving data were handled. Review their approach to security, secrets, infrastructure as code and monitoring, not only their Python code. Language expectations should be agreed early for teams in Austria, especially when operational runbooks and incident communication must be shared across locations.
Frequently asked questions
Key details about Apache Airflow, drawn from the questions we get asked most.
Apache Airflow is used to schedule, coordinate and monitor workflows made up of dependent tasks. Companies commonly use it for data ingestion, warehouse transformations, quality checks, machine learning pipelines and recurring operational processes.
Apache Airflow provides a richer control layer than cron, including dependency management, retries, backfills, logs and a user interface. Compared with managed services such as AWS Step Functions, Google Cloud Composer or Azure Data Factory, it offers broad Python-based orchestration and portability, while requiring more operational ownership when self-hosted.
A strong Apache Airflow specialist usually also understands Python, SQL, data warehouses, cloud storage and containerized deployment. Experience with Kubernetes, Apache Spark, dbt, CI/CD, secrets management and observability is valuable when workflows run in production.
The right level depends on the scope, risk and operating model of the workflow. A professional handling production orchestration should be able to explain DAG design, scheduling behavior, recovery procedures, testing and monitoring through concrete delivery examples, not only training exercises.
Yes. Apache Airflow has a web interface, centralized logs and declarative workflow definitions that support remote collaboration. Teams in Austria should still agree on time zones, documentation language, access procedures and who responds when a scheduled workflow fails.
Apache Airflow may be a poor fit for low-latency event processing, simple single-step schedules or workflows that require continuous streaming rather than batch orchestration. In those cases, event brokers, stream processors or a simpler scheduler may be more appropriate.
Ask how the Apache Airflow professional would handle retries, idempotency, backfills, late data, schema changes and failed dependencies. A high-quality specialist also discusses observability, security, deployment processes and maintainable DAG structure before proposing implementation work.
An Apache Airflow freelancer may deliver DAGs, provider integrations, deployment configurations, monitoring rules, data quality controls and operational documentation. They may also review an existing environment, migrate scripts into managed workflows or establish standards for testing and release.
The average hourly rate of freelancers in Austria who have used Apache Airflow in their recent projects is 102 €, which corresponds to a daily rate of about 817 € based on an 8-hour working day.
Of the freelancers in Austria 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 Austria who have used Apache Airflow in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 1.5 years.
The most common languages among freelancers in Austria who have used Apache Airflow in their recent projects are German (100%), English (100%), and French (29%).
The most common industries among freelancers in Austria who have used Apache Airflow in their recent projects are Banking and Finance (71%), Information Technology (71%), and Education (57%).
The most common business areas among freelancers in Austria who have used Apache Airflow in their recent projects are Business Intelligence (100%), Information Technology (100%), and Product Development (71%).
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.
Countries:
- Germany
- Austria
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