Big Data Experts in Vienna
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Meet FRATCH Experts in Vienna, who have recently used Big Data
Alexander P.
Last position:
Owner & Lecturer at Own company for AI governance and data products, Vienna
- Consulting and interim management at the interface between IT operations and regulation
- Impact analysis and implementation planning for NISG 2026 and the EU AI Act, including risk management and reporting and evidence processes
- Training for governing bodies and employees on regulatory obligations
- Lectures in Data & Information Management and Human-Machine Interaction at University of Applied Sciences Burgenland, since 2023
- Supervision of master’s theses and participation in the examination board
- Presentations for business and educational institutions
- Design and development of data and AI products, platforms and pipelines
- Privacy-first architectures and zero-knowledge encryption, cloud-native on EU infrastructure
- MLOps and AIOps in live operations
- Own applications under own brand: shared codebase, separate delivery for each target device
- AI-assisted software development (vibe coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
- Publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
- Publications on data sovereignty, cloud economics and industrial image processing
- AI governance / compliance: data quality, Responsible AI, EU AI Act readiness, risk classification, AI ethics
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)
Axel M.
Last position:
Interim HR Lead Transformation – International E-Commerce & Logistics Environment at Inpact HR (Interim Management)
- Organizational Design: Strategic realignment of the organizational structure to increase operational excellence and prepare for a scaled shared service model.
- Tech-Driven HR Transformation: Supporting process optimization through the integration of modern automation solutions and AI-powered tools to increase efficiency in workforce management.
- Strategic Change & Rightsizing: Design of a change-management framework to align personnel resources with a new, centralized steering model.
Fabio G.
Last position:
IT Architect, Requirements Analyst and Consultant at CANCOM
- Supports CANCOM customers in migrating legacy on-prem systems to Microsoft Fabric and Microsoft Foundry
- Takes over and stabilizes existing solutions after a short handover
- Business analysis and requirements engineering for migration to a new cloud environment
- Optimization of machine learning models for feature extraction and customer profiling
- Ensures data protection and compliance
- Leads the migration of on-prem systems to Microsoft Fabric
- Designs new AI platforms for clients
- Tests the integration of chatbots for document intelligence with Microsoft Foundry, including requirements analysis, implementation, validation, and client communication
Michael G.
Last position:
Scrummaster at Xenovo
Planning and monitoring sprints and holding the scheduled meetings
Analyzing and resolving issues in the development process
Error analysis, bug management and correction in individual process steps
Stakeholder management
Documentation and improvement of the development process
Tools: JIRA, Confluence
Stéphane L.
Last position:
Expert BI Consultant at Freelance
- Project management
- Design, optimization, query, reporting, and data modeling
- Liaising with clients / training
- Design, optimization, and development of query, reporting, and data architecture
- SAP SAC
- Story
- Data Action
- Planning
- SAP Datasphere
- SAP BTP
- MS Power BI
- DAX
- Power Query
- IBM Cognos Reporting
- Framework Manager
Attila D.
Last position:
Full-Stack Software Engineer at Research Data Evaluation
- Custom anonymized research data analyzer, providing insights and facilitating data-driven decision-making.
- Designed and developed back- and frontend.
- Delivered end-to-end solution.
- Accelerated research timeline by 2 months.
Peter K.
Last position:
Sabbatical
Gasper Z.
Last position:
Senior BI Consultant at PMONE GmbH
Robert P.
Last position:
Editorial Lead, Falstaff International Online at Falstaff Verlag
Discover over 15,000 top freelancers
Statistics of experts using Big Data
Aggregated from the professional profiles of matched freelancers.
Experience
26 years
Position duration
3 years
Positions per freelancer
12
Top business areas
Project Management, Information Technology, Business Intelligence
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Project Management, Business Intelligence, Human Resources
Bachelor's degree or higher
90%
Master's degree or higher
80%
Doctorate
10%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
100%
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 Vienna 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 Vienna using Big Data
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.
Big Data 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 (70%)
- Professional Services (60%)
- Banking and Finance (50%)
- Education (40%)
- Transportation (40%)
- Manufacturing (40%)
- Media and Entertainment (40%)
- Telecommunication (30%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Big Data covers
Big Data refers to methods and systems for collecting, storing, processing and analysing data at a scale or speed that traditional databases cannot handle efficiently. It supports batch processing, real-time events, machine learning workflows and operational analytics across structured and unstructured sources.
What it builds
Companies use Big Data to create data platforms that connect business systems, sensors, applications and customer interactions. Typical deliverables include:
- Data lakes and lakehouse environments
- Streaming pipelines for events and telemetry
- Distributed analytics and reporting layers
- Feature pipelines for machine learning
Ecosystem and tooling
The Hadoop ecosystem remains relevant for distributed storage and processing, while Apache Spark is widely used for batch analytics and data preparation. Apache Kafka supports event streaming, with tools such as Apache Flink, Hive, Trino, Airflow, Databricks and cloud data services extending the stack. Strong specialists also work with Python, SQL, Java or Scala, containers and infrastructure automation.
When companies need specialists
Freelance expertise is useful when an organisation is moving from isolated databases to a shared data platform, replacing fragile pipelines or introducing real-time processing. It is also valuable during cloud migration, merger integration, analytics modernisation or a machine learning rollout. In Vienna, remote collaboration can work well, while regulated or operational environments may require local workshops and German or English communication.
Delivery and reliability
Good Big Data work starts with clear data ownership, source assessment and measurable quality rules. Professionals should design for schema changes, late events, duplicate records, failure recovery and controlled access rather than focusing only on throughput. They should also document lineage, tests, deployment steps and operating responsibilities so internal teams can maintain the result.
Choosing the right professional
Look for specialists who can explain trade-offs between batch and streaming, warehouse and lakehouse, managed services and self-hosted components. Ask for examples of production pipelines, incident handling and cost-aware architecture, not only tool names. The strongest professionals connect technical decisions to reporting accuracy, service reliability, privacy requirements and the people who will use the data.
Frequently asked questions
Key details about Big Data, drawn from the questions we get asked most.
Big Data is used to collect and process large, fast-changing or varied datasets for analytics, forecasting, automation and operational decisions. Common applications include customer behaviour analysis, fraud detection, logistics optimisation, industrial monitoring and machine learning.
Big Data systems distribute storage and processing across multiple resources and can handle high-volume, high-velocity or unstructured inputs. A traditional database or warehouse is often better for tightly defined transactional workloads and governed reporting, so many companies use both rather than choosing one exclusively.
A strong Big Data specialist usually combines distributed processing with SQL, Python, Java or Scala, cloud services, data modelling and workflow orchestration. Experience with Apache Kafka, Apache Spark, data quality, security, infrastructure automation and machine learning pipelines can be important depending on the assignment.
The right level depends on whether the work involves a new platform, a focused pipeline or support for an existing environment. Big Data projects need someone who has handled production concerns such as data quality, failure recovery, schema evolution and monitoring, not only classroom examples.
Yes, much Big Data work can be delivered remotely when access, documentation and communication channels are well prepared. On-site sessions in Vienna can still help with source-system discovery, stakeholder workshops, security reviews or coordination with teams operating physical infrastructure.
Apache Spark is often chosen for fast batch analytics, data preparation and iterative workloads, while Hadoop components can provide distributed storage and resource management in established environments. The best choice depends on existing systems, workload patterns, cloud strategy and the team’s operating skills.
Ask a Big Data professional to show how they test pipelines, track lineage, handle bad or late data and recover from failures. Quality is visible in reliable outputs, understandable documentation, controlled access, useful monitoring and an architecture that remains manageable after handover.
A Big Data assignment in Vienna may involve financial services, manufacturing, transport, public services or research, each with different data controls and collaboration habits. Freelancers should clarify language expectations, remote and on-site requirements, access procedures, cloud permissions and who owns decisions about data quality and security.
The average hourly rate of freelancers in Vienna, Austria who have used Big Data in their recent projects is 104 €, which corresponds to a daily rate of about 836 € based on an 8-hour working day.
Of the freelancers in Vienna, Austria who have used Big Data in their recent projects, 90% hold at least a Bachelor's degree, 80% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers in Vienna, Austria who have used Big Data in their recent projects have 26 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Vienna, Austria who have used Big Data in their recent projects are German (100%), English (100%), and French (50%).
The most common industries among freelancers in Vienna, Austria who have used Big Data in their recent projects are Information Technology (70%), Professional Services (60%), and Banking and Finance (50%).
The most common business areas among freelancers in Vienna, Austria who have used Big Data in their recent projects are Project Management (100%), Information Technology (90%), and Business Intelligence (70%).
Main locations of FRATCH Experts, who have recently used Big Data
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:
Vienna 
Graz Request a free demo
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