Data Pipeline Experts in Austria
matched in minutes from over 15,000 CVsHire experts who design ETL and ELT workflows, connect cloud and enterprise data sources, and deliver reliable batch or streaming pipelines. FRATCH finds precise matches with vetted, available freelancers quickly.
Meet FRATCH Experts in Austria, who have recently used Data Pipeline
Karl F.
Last position:
ONECEPT Website at ONECEPT GmbH
Development and implementation of the website onecept.at using React/Next.js. Focus on responsive web design, high-performance component structure, basic SEO optimization, and technical deployment.
Technologies: React, Next.js, TypeScript / JavaScript
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.
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.
Nikolaus J.
Last position:
Solution Architect at HIT Baumärkte
- Leading high-impact retail digital transformation focused on data integration, app integration, and next-generation customer engagement strategies.
Daniel A.
Last position:
Solution Architect and Fullstack Developer at IoT Sensor Data Processing and Evaluation
- Develop a concept for the analysis of sensor data.
- Assess implementation options, products, and pricing in Azure.
- Present and advocate the solution concept to the client.
- Implement an ETL pipeline for processing sensor data.
- Integrate BI solutions with the data repository.
- Provide documentation and support for end users.
Hossein A.
Last position:
Datawarehouse Consultant at LENZING AG
- Consulting on the enterprise data-warehouse and reporting practice at one of Austria's largest industrial groups.
- Designing and standardizing Power BI dashboards and data-visualization governance for company-wide enterprise reporting.
- Developing a WCAG-compliant, colorblind-safe visualization standard (Okabe-Ito palette) to harmonize dashboards across the organization.
Armin F.
Last position:
Head of AI & Data Science at Ascent DACH
- Lead architect for AI and ML projects including GenAI, LLM-based apps and forecasting solutions
- Guided customers through solution scoping, architecture design, and PoCs across various industries (Pharma, Insurance, Logistics, FMCG)
- Delivered production ML pipelines using Azure ML, MLflow, and MLOps best practices
- Responsible for effort estimation, delivery and staffing of 5 – 10 projects simultaneously
- Hiring manager for the data science and AI team and responsible for creating the technological offering and roadmap in the AI & Data Science space
- Built and scaled the AI/Data Science service offering from scratch to a high 6-figure annual revenue with 30+ successful deliveries and 20+ clients
- Regular speaker at AI and data science conferences and academic institutions
Elija L.
Last position:
Consultant at Fujitsu Deutschland Mediashop GmbH
- Support and co-design of the development and evolution of an enterprise-wide HUB system for integrating various data warehouse and BI systems as well as data sources and applications in an international context
- Consulting and analysis in the area of enterprise-wide data and BI systems, including organizational structure, data flows, system landscapes, architecture, and strategic data integration
- Data modeling, ETL processes, reporting, and data quality management
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 Data Pipeline
Aggregated from the professional profiles of matched freelancers.
Experience
10 years
Position duration
1.7 years
Positions per freelancer
10
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Education, Manufacturing
Certification focus areas
Information Technology, Business Intelligence, Marketing
Bachelor's degree or higher
89%
Master's degree or higher
67%
Doctorate
11%
Certifications per freelancer
3
Most common languages
English, German, Spanish
Speak two or more languages
90%
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 Austria 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 Austria using Data Pipeline
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.
Data Pipeline 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 (90%)
- Education (50%)
- Manufacturing (50%)
- Media and Entertainment (50%)
- Retail (50%)
- Banking and Finance (40%)
- Professional Services (40%)
- Healthcare (30%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Data Pipelines Do
A data pipeline moves information from source systems to destinations where it can be analysed, operationalised or stored. It can collect events in real time or process scheduled batches. Typical outcomes include trusted data warehouses, reporting layers, machine learning datasets and operational data services.
Core Pipeline Patterns
Pipelines may follow ETL, ELT, change data capture or event-driven designs. Strong specialists select the pattern according to data volume, latency, governance and recovery needs. They define schemas, transformations, dependencies and clear ownership from ingestion through consumption.
Ecosystem and Tooling
The work can span relational databases, APIs, files, message brokers and SaaS systems. Common tooling includes Apache Airflow, Dagster, dbt, Apache Kafka, Spark, Snowflake, Databricks and cloud services from AWS, Microsoft Azure or Google Cloud. SQL, Python, containerisation and infrastructure automation often support the pipeline.
Where Companies Use Them
- Consolidating finance, sales and customer data for reporting
- Feeding data warehouses, lakehouses and analytics platforms
- Streaming events into monitoring or personalisation systems
- Preparing governed datasets for machine learning
- Replacing fragile scripts with observable workflows
Pipelines appear in manufacturing, retail, logistics, financial services, healthcare and public-sector environments. The design must reflect the organisation’s source systems, security model and operating constraints.
When Freelance Expertise Helps
Companies often bring in a specialist during a migration, platform rebuild or integration-heavy product launch. External expertise is also useful when failed jobs, duplicate records, slow loads or unclear lineage make existing data unreliable. In Austria, remote collaboration can work well when documentation and access processes are established; on-site work may help with complex legacy environments and stakeholder workshops.
What Quality Looks Like
Reliable professionals build idempotent jobs, useful tests, alerting, retry logic and clear runbooks. They monitor freshness, completeness, latency and cost instead of treating a successful run as proof of quality. They also understand access controls, privacy requirements, schema evolution and how business users will validate the resulting data.
Frequently asked questions
What clients ask us most about Data Pipeline — answered in short.
A Data Pipeline transfers and transforms information between systems so it can support analytics, reporting, applications or machine learning. It can combine databases, APIs, files, event streams and SaaS sources while applying validation and business rules.
An ETL pipeline extracts data, transforms it before loading, and is common where the destination has limited transformation capacity. ELT loads raw data first and transforms it in the warehouse or lakehouse. Data pipeline is the broader term and can include both approaches, as well as streaming workflows.
A strong Data Pipeline specialist usually works confidently with SQL, Python, cloud storage, databases and orchestration tools. Experience with Apache Airflow, dbt, Apache Kafka, Spark, data modelling, testing and infrastructure automation is also valuable.
A Data Pipeline project needs a specialist whose background matches its sources, destinations, latency and governance requirements. A straightforward scheduled integration may need focused implementation skills, while a regulated streaming platform or migration needs deeper design, observability and incident-handling experience.
Yes, Data Pipeline work is often suitable for remote collaboration because development, testing and monitoring are conducted through shared cloud and version-control environments. On-site sessions can still be useful for access approvals, legacy-system discovery and workshops with data owners.
Review whether the Data Pipeline has automated tests, documented dependencies, safe retries, monitoring and a clear recovery process. Ask how the specialist handles duplicate records, late data, schema changes, access control and failures that affect downstream users.
A Data Pipeline should use streaming when users or systems need events with low delay, such as operational alerts or live personalisation. Batch processing is often simpler and more economical for periodic reporting, large historical loads and workloads without immediate freshness needs.
A Data Pipeline specialist should clarify source ownership, data contracts, destinations, freshness expectations, security rules and acceptance criteria. They should also confirm deployment practices, monitoring responsibilities, access to representative data and how business stakeholders will verify correctness.
The average hourly rate of freelancers in Austria who have used Data Pipeline in their recent projects is 101 €, which corresponds to a daily rate of about 810 € based on an 8-hour working day.
Of the freelancers in Austria who have used Data Pipeline 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 Austria who have used Data Pipeline in their recent projects have 10 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Austria who have used Data Pipeline in their recent projects are English (100%), German (90%), and Spanish (20%).
The most common industries among freelancers in Austria who have used Data Pipeline in their recent projects are Information Technology (90%), Education (50%), and Manufacturing (50%).
The most common business areas among freelancers in Austria who have used Data Pipeline in their recent projects are Business Intelligence (100%), Information Technology (100%), and Product Development (70%).
Main locations of FRATCH Experts, who have recently used Data Pipeline
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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FRATCH CEO
