Data Quality Experts in Austria
for reliable data pipelines, matched in minutes with vetted professionalsHire experts who profile, validate and monitor business data across CRM, ERP and analytics systems. Work with specialists who improve accuracy, completeness and consistency while integrating quality checks into everyday data operations. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Austria, who have recently used Data Quality
Alexander P.
Last position:
Owner & Lecturer at Artellico / Own company for AI governance and data products
- Consulting and interim management at the intersection of IT operations and regulation
- Impact assessment 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
- Teaching assignments in Data & Information Management and Human-Machine Interaction at Hochschule Burgenland, since 2023
- Supervision of Master's theses and participation on examination boards
- Industry talks for businesses 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
- Integration with bank account systems using SEPA direct debit mandates and message formats under ISO 20022 (pain.008, camt.053)
- MLOps and AIOps in live operations
- Own applications under my own brand: shared codebase, separate deployment for each target device
- AI-assisted software development (vibe-coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
- Professional publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
- Professional 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
Thomas P.
Last position:
Change Manager / AI-driven Finance Transformation at Agrana
Organizational Change Management for the strategic setup of a hybrid GBS rollout as part of a global, AI-driven Finance Transformation. End-to-end management of the OCM architecture in a highly complex on-, near-, and offshore partner setup [IN, PL, RO]. Successful completion of Phase 1 (Initial Strategy) and strategic pausing by the Executive Board after the early disclosure of critical vendor-side OPEX risks
Systemic Baseline Assessment & Stakeholder Diagnostics: Evaluation of the global organization and analysis of the process landscape across 21 countries [AT, DE, CH, FR, UK, SI, RO, UA, RU, US, CD, CN, AR, MX, ZA, IN, JP] to precisely determine change requirements
Architecting the OCM Strategy & Master Roadmap: Independent development of a comprehensive, AI-centered Change Roadmap for end-to-end management of all change initiatives across every project phase
Data Quality & AI Agent Risk Mitigation: Auditing of Process Data Repositories (Celonis analysis); prevention of the ingestion of 58% synthetic training data to safeguard AI model reliability amid geopolitical supply chain tensions
GBS Vendor BAFO Triage & Contractual Commitment: Critical review of Tier-1 vendor pitches and contractual commitment to a reduced Non-STP rate (from 7% to 4%) to avoid extreme manual rework with a planned FTE reduction (-63%)
Executive Enablement & Board Alignment: Design of the GBS Transformation Executive Board Deck to strategically enable C-level executives and transparently present completely overlooked AI tokenization costs
Targeted Change Communications & Engagement: Design and development of audience-specific communication measures to align the highly diverse, globally distributed stakeholder network
Adoption Velocity & Resistance Measurement: Engineering of quantitative measurement tools (Pulse Check Survey) using Behavioral Dyads to identify resistance based on data and ensure sustainable success measurement
Results:
- Avoidance of disruptive misallocations: Stopping the ingestion of 58% synthetic AI-agent training data after discovering only 42% compatibility with existing processes, preventing critical GBS cascade errors
- Significant OPEX & effort reduction: Reduction of the Non-STP rate in Tier-1 vendor BAFOs from 7% to 4% alongside an impending 63% Finance-FTE reduction; avoidance of thousands of time-consuming manual correction processes
- 100% Delivery of the OCM architecture & ROI protection: Delivery of all OCM artifacts (Change Roadmap, Comms Plan, Executive Board Deck, Pulse Check Survey) and protection of ROI by identifying incalculable LLM runtime token costs
Octavian G.
Last position:
Oracle DWH Analyst at Infomotion Gmbh
Oracle PL/SQL, Oracle SQL, ITIL
Zeev T.
Last position:
Enterprise Architect at Coveris Group
- Built Enterprise Architecture practice covering business, application, data, and integration layers
- Created a multi-year Integration Strategy, delivering annual cost savings of several hundred thousand euros
- Defined portfolio simplification roadmap, identifying redundant systems and cost reduction opportunities
- Designed target-state enterprise architecture around D365 FSCM, enabling a best-of-breed future landscape
- Developed Master Data Management (MDM) strategy and roadmap to improve data quality and operational efficiency
- Provided enterprise-wide architectural direction ensuring alignment and eliminating redundant initiatives
- Established reusable architecture patterns adopted by delivery teams
- Facilitated cross-functional architecture forums to align product and delivery teams
- Translated enterprise architecture guidance into practical delivery decisions
- Drove practical adoption of architecture guidance across initiatives rather than acting as a gatekeeper
- Identified redundant systems enabling substantial cost reduction potential
- Enabled cost transparency in integration landscape
- Enabled fact-based investment prioritization decisions
Elija L.
Last position:
Fujitsu Deutschland
- Supporting and helping shape the development and further development of a company-wide HUB system in the Fujitsu environment for integrating a wide range of data sources and applications in an international context
- Design and implementation of data modeling, ETL processes, reporting, and data quality management
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).
Shahram F.
Last position:
Senior Product Owner at Elderly Neighbour Watch
Delivery of a digital, non-profit neighborhood platform connecting older people with volunteers for practical support and social companionship. Responsibility for business analysis, requirements definition, platform evaluation and delivery of a locally scalable service solution, with a focus on AI-supported development, data-driven optimization and clear market positioning. Evaluation of several low-code/business platforms, including Odoo and Glide Apps, as well as assessment of monday.com as a CRM-related option, before selecting Glide Apps for implementation. Implementation of a non-native mobile and desktop application with Glide Apps and the website with WordPress. Responsibilities
- Gathering, analyzing and structuring business requirements for the product and service model
- Conducting market, target group and competitor analyses to position the offering
- Evaluating and selecting suitable low-code/business platforms for implementation
- Defining key user journeys, business processes and operational workflows for older people, volunteers and Administration
- Translating business requirements into requirements for profiles, task management, coordination, communication and notifications
- Supporting the implementation of the non-native mobile and desktop application in Glide Apps and the website in WordPress
- Preparing future AI-supported functions such as intelligent matching and data-driven optimization
- Ensuring compliance with GDPR requirements Results
- Successfully delivered digital support platform connecting older people with volunteers
- Solid foundation for market positioning through market, target group and competitor analyses
- Implemented functional non-native mobile and desktop application with Glide Apps and accompanying website with WordPress
- Created foundation for scaling and AI-based further development
Christian P.
Last position:
Migration Lead for Accounting & Year-End Closing Tests at Raiffeisenverband Salzburg
- Project and test management for the accounting migration
- Coordination of resources
- Planning, creation and alignment of scenarios with functional experts and IT product owners
- Responsibility for accounting KPIs of the migration cockpit
- System environment: Jira, XRay, Confluence
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
Gerald G.
Last position:
Data Design Authority at Department of Government Enablement
- Responsible for realigning the data architecture of the Abu Dhabi government to achieve a fully AI-driven public administration
- Definition of modeling standards
- Creation of a conceptual and logical model for the entire Abu Dhabi government administration
- Definition of data quality and data security standards
Alexander T.
Last position:
Functional Analyst & Administrator at Netz Niederösterreich GmbH
- Introduced automated testing for Fabasoft components and trained testers to create automated test cases.
- Installed AppTest on the server and clients.
- Requested firewall exceptions to allow communication between the AppTest server and clients.
- Conducted training sessions for testers.
- Automated test workflows.
- Created reports and sent emails.
- Enabled faster reviews of new releases, reduced manual testing effort, and improved documentation of test results and discovered defects.
Johanna U.
Last position:
Manager at Deloitte Consulting GmbH
- Technology consulting and project management focused on SAP ICMR and SAP Group Reporting
Qamile B.
Last position:
SAP BI / SAP Analytics Cloud at ARDDEX Group
- Gathering requirements and conceptually designing reporting and planning requirements in controlling (CO) and modeling SAP Analytics Cloud data models for group reporting.
- Designing and implementing reports and dashboards to support planning, forecasting and control processes.
Franz P.
Last position:
Business & IT Consulting at fpcon Franz Plakolm Consulting
- Business consulting finance & supply chain for Infor ERP LN Cloudsuite projects
- Lead consultant ERP LN Cloudsuite finance & cost accounting
- Implementation projects in Germany for a manufacturer of precision castings and a producer of stainless steel kegs
- Optimization project at a steel service center
Discover over 15,000 top freelancers
Statistics of experts using Data Quality
Aggregated from the professional profiles of matched freelancers.
Experience
24 years
Position duration
2.7 years
Positions per freelancer
15
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Banking and Finance, Information Technology, Professional Services
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
82%
Master's degree or higher
64%
Doctorate
9%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
100%
Based on our profile pool as of 29 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 Data Quality
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Data Quality 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 (86%)
- Information Technology (86%)
- Professional Services (57%)
- Government and Administration (57%)
- Telecommunication (43%)
- Automotive (36%)
- Transportation (36%)
- Manufacturing (36%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Data Quality Covers
Data Quality is the discipline of making data accurate, complete, consistent, timely and fit for its intended use. Specialists examine how information is collected, transformed, stored and consumed across business systems. Their work supports dependable reporting, automation, analytics and regulatory processes.
Typical Deliverables
Companies use Data Quality expertise to turn unreliable records into usable information. Common deliverables include:
- Data profiling and quality assessments
- Validation rules for incoming and transformed data
- Duplicate detection, matching and record consolidation
- Monitoring dashboards, issue queues and quality reports
Ecosystem and Tooling
Data Quality work connects SQL, spreadsheets, databases and cloud data platforms with governance and integration processes. Specialists may work with Great Expectations, Soda, dbt tests, Monte Carlo, Informatica or Talend, depending on the environment. They also use Python, APIs and workflow tools to automate checks and route exceptions.
When Companies Need Help
Freelance expertise is valuable when data problems slow a migration, weaken dashboards or create conflicting customer and product records. It can also support a new warehouse, master data initiative or CRM rollout. In Austria, specialists often collaborate remotely with international teams and join on-site workshops when processes and ownership need close alignment.
Skills That Matter
Strong professionals combine technical investigation with a clear understanding of business definitions. They can trace defects to their source, distinguish a real issue from an intentional exception and translate findings into practical controls. Experience with data governance, metadata, lineage, ETL or ELT pipelines, SQL and stakeholder communication adds depth.
Choosing a Specialist
Look for evidence of measurable improvements in the same data domain, not only tool familiarity. A capable specialist explains quality dimensions, defines acceptance criteria and makes recurring checks maintainable after handover. Ask how they handle sensitive information, document rules and coordinate with teams using the data. Clear communication in English and, where needed, German can simplify collaboration with Austrian organizations.
Frequently asked questions
Before you brief your next project: the most common questions about Data Quality.
Data Quality is used to assess and improve the accuracy, completeness, consistency, timeliness and validity of information. Companies apply it to CRM records, financial data, product catalogs, operational systems, data warehouses and analytics pipelines.
Data Quality is broader than data cleansing. Cleansing corrects, standardizes or removes problematic records, while Data Quality also covers profiling, validation, monitoring, ownership, definitions and the controls that prevent issues from returning.
A strong Data Quality specialist often brings SQL, data profiling, ETL or ELT knowledge and experience with databases or cloud warehouses. Useful adjacent skills include master data management, data governance, metadata, lineage, Python and business process analysis.
The right Data Quality freelancer depends on the scope and risk of the work. A focused validation review may need a specialist familiar with one system, while a cross-business program requires experience with governance, multiple data domains, stakeholder alignment and sustainable monitoring.
Data Quality work is often well suited to remote collaboration because specialists can inspect schemas, rules, pipelines and reports securely. Workshops with data owners or process teams may still benefit from on-site sessions in Austria, especially during discovery and rollout.
Ask how the Data Quality specialist defines quality dimensions, prioritizes defects and proves that controls work. Strong answers include traceable root-cause analysis, documented rules, clear ownership, useful monitoring and a plan for maintaining checks after delivery.
Data Quality projects may use Great Expectations, Soda, dbt tests, Informatica, Talend or Monte Carlo alongside SQL and Python. The best choice depends on the data stack, integration patterns, security model and whether checks must run in pipelines or as ongoing monitoring.
Working with Data Quality usually means investigating unclear definitions, tracing issues across systems and agreeing on practical rules with business and technical teams. Freelancers should expect a mix of analysis, documentation, testing, stakeholder discussions and follow-up monitoring rather than one isolated cleanup exercise.
The average hourly rate of freelancers in Austria who have used Data Quality in their recent projects is 113 €, which corresponds to a daily rate of about 905 € based on an 8-hour working day.
Of the freelancers in Austria who have used Data Quality in their recent projects, 82% hold at least a Bachelor's degree, 64% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers in Austria who have used Data Quality in their recent projects have 24 years of professional experience, with a single engagement typically lasting around 2.7 years.
The most common languages among freelancers in Austria who have used Data Quality in their recent projects are German (100%), English (100%), and French (36%).
The most common industries among freelancers in Austria who have used Data Quality in their recent projects are Banking and Finance (86%), Information Technology (86%), and Professional Services (57%).
The most common business areas among freelancers in Austria who have used Data Quality in their recent projects are Information Technology (100%), Business Intelligence (93%), and Product Development (71%).
Main locations of FRATCH Experts, who have recently used Data Quality
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.
Vienna Graz 
Vienna Countries:
- Germany
- Austria
- Switzerland
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Philipp Thomaschewski
FRATCH CEO
