Data Quality Experts in Switzerland
to make business data reliable, with precise AI matching and vetted, available freelancersHire experts who improve data accuracy, completeness and consistency across CRM, ERP and analytics environments. Work with specialists in data profiling, validation rules, remediation and governance, matched quickly to your needs from vetted, available freelancers.
Meet FRATCH Experts in Switzerland, who have recently used Data Quality
Tomas H.
Last position:
Senior Advisor at Private Equity company (Business Integration)
Engaged to build governance, risk and process-improvement capabilities from scratch across approximately 30 fast-growing, decentralised lines of business in Germany, driving quality and productivity gains across business and functional teams.
- Applied Six Sigma root-cause analysis methodology (5-Why, Fishbone/Ishikawa) to lead investigations and process-improvement initiatives across the organisation’s finance, risk, IT and procurement functions, driving corrective actions and process redesign through to verified, sustained closure.
- Delivered structured training programmes to approximately 1,200 employees, for Compliance topics, incl. Six Sigma analysis and process-improvement methodology, building a continuous-improvement mindset and self-assessment capability across business and functional leaders.
- Analysed and optimized finance, risk and procurement processes across approximately 30 decentralised lines of business, developing and implementing continuous-improvement strategies and collaborating with cross-functional stakeholders (Finance, Controlling, IT, Procurement) to achieve measurable quality and productivity gains.
Gwang Jin K.
Last position:
Data Scientist / Applied AI, Automation & Data Systems Researcher at Independent
- Built and explored applied GenAI, RAG, GraphRAG, local LLM, agentic AI and document-intelligence prototypes for structured analysis, evidence extraction, semantic search, technical reasoning and decision-useful reporting
- Developed private local-LLM workflows and AI system patterns focused on privacy, reproducibility, reviewability, low-cost inference and practical user control
- Built reproducible Python/R workflows for data analysis, automation, API-driven tooling, validation logic, technical documentation and AI-assisted software development
- Designed workflows around explicit assumptions, traceable inputs, reviewable outputs and failure-mode awareness rather than black-box “looks good” demonstrations
- Supported RAHN AG in a chemical/regulatory environment with data extraction and processing around WERCS, a regulatory application for chemical product and compliance data
- Explored complex application/database schemas and wrote nested SQL queries to extract information for mixture calculations, component relationships, regulatory rules and reporting logic
- Continued hands-on development in Git/GitHub/GitLab/Bitbucket, Docker/Linux deployment patterns, REST/API workflows, error handling, technical writing and fast AI-assisted prototyping
- Built technical writing and documentation workflows that turn complex systems into clear runbooks, checklists, decision notes and user-facing explanations
Lenka P.
Last position:
Workday Technical Architect at Swisscom
(Project Assignment via consulting company HighPerfPeople)
- Lead the Workday Optimization Board, defining and presenting the Workday enhancement roadmap; drive prioritization based on stakeholder input, system analysis, and identified capability gaps.
- Challenge business requirements and proposed solutions to ensure alignment with long-term architecture principles, platform strategy and operational sustainability.
- Own the complete lifecycle of Workday enhancements from business discovery and solution design through implementation governance, testing strategy, deployment and stabilization.
- Act as functional/technical lead for key product areas including Peakon, Workday Learning, and Talent/Performance processes (e.g., year-end cycle, goal setting).
- Define and implement Workday branding and communication standards (templates, notification design, messaging structure) to improve consistency and employee experience.
- Build and enhance manager- and HR-facing tools (reports, dashboards, guidance/Journeys, process support assets) to reduce manual effort and improve decision-making.
- Translate complex system behavior, security/privacy constraints, and process implications into clear options for business stakeholders and leadership.
- Drive cross-functional collaboration with HR process owners, IT/security, and vendors to resolve issues and enable scalable solutions.
- Strong focus on adoption: ensure changes are usable, understandable, and actionable for employees, managers, and HR teams.
Kawahya T.
Last position:
Public Health Expert - Contract at Mercor
- Contributed to Project Atlas as a domain expert supporting the design of realistic, long-horizon professional tasks for AI agent evaluation. Developed complex, public health-relevant workflows that test an AI agent's ability to navigate ambiguous prompts, synthesise information across distributed files and systems, manage multi-step dependencies, handle errors, and produce high-quality professional deliverables.
- Applied public health expertise to design task scenarios involving emergency preparedness, operational readiness, health systems strengthening, risk assessment, surveillance, and policy-oriented decision-making. Responsibilities included creating task prompts, golden solutions, rubrics, and evaluation criteria aligned with real-world professional standards. At the same time, ensuring outputs were action-focused, ethically grounded, and suitable for assessing advanced AI performance in realistic organisational environments.
Monika E.
Last position:
Tax Specialist at Julius Bär / Bosshard & Partner
- Operational responsibility in tax relief at source
- Took over and stabilized a complex department during a project phase
- Analysis, review, and optimization of existing processes and workflows
- Updating and further development of the specialist manual
- Analysis and resolution of individual cases in an international tax environment
Peter W.
Last position:
IT Consultant at WYP-Consulting
Mandy G.
Last position:
Founder & Principal Consultant at MGH Consulting
- Established an independent consulting practice offering transformation, strategy, AI enablement and operational design to organisations across Switzerland and internationally
- Delivering pro-bono and paid engagements with NGOs, foundations, trusts and SMEs across Switzerland
- Service offering spans governance design, digital transformation, AI tools training and data visualisation
- Building a Swiss-based team with a vision to employ internationally experienced consultants
Hanspeter J.
Last position:
Lead Salesforce Consultant DACH at DXC Technology
- Recording, validating, and coordinating customer requirements
- Analyzing customers' business processes, and designing and implementing solutions in Salesforce
- Designing and developing Salesforce architectures using Sales and Service Cloud
- Maintaining and expanding my skills to stay current with Salesforce's new features
- Taking an active role in the pre-sales phase and working closely with sales and pre-sales teams
- Building and strengthening the team's expertise in new areas
- Actively helping to define and align my role within DXC's best practices
- MC Growth implementation
- AI Agentforce Agents Builder
- Agent Designer with elements.cloud
- Salesforce org assessments
- Process configuration mining
- Serving as a single point of contact for global SFDC contacts
- Coordinating projects with the EMEA and global headquarters
- Preparing proposals and presales work with Salesforce Account Executives and client partners for global accounts
Max M.
Last position:
Qualtrics CXM Solutions Expert at Freelancing
Support with the introduction and implementation of the Qualtrics XM platform in the consulting and service environment for customers, e.g. in the banking sector, focusing on data quality, parameterization, technical coordination, and implementation support
Technical validation of configurations, feedback flows, and reporting setups
Review and assurance of data quality (mapping, mandatory fields, regulatory-relevant fields)
Performance of UAT, functional tests, and data checks in collaboration with the department and IT
Coordination with stakeholders from consulting, service, compliance, IT, and product management
Clarification of technical requirements with the business side and derivation of adaptation requirements in the platform
Creation of documentation, test protocols, and quality-related artifacts
Support in the preparation of internal approvals and rollouts
Successful technical acceptance of the new feedback and reporting functionalities
Increase in data quality in the relevant fields (e.g., feedback classification, assignment to the consulting process)
Stable implementation of the platform in the consulting environment with clear handover to IT and specialist departments
Reinhold S.
Last position:
Senior Software Developer at Hitachi Energy
- Support and further development of the Leegoo Builder
- Handling ad hoc requests
- Definition of rules/attributes and their rules
- Optimizing and managing SQL queries
Daniel S.
Last position:
Senior Manager at devpoint GmbH
- Design and co-implementation of an insolvency management platform in Germany for a client (based on an AI development tool)
- Concept, requirements engineering, and implementation support for a Dubai-based company to integrate processes into a CRM
- Business analysis and requirements engineering at Swisscom for integrations
- Integration of a new knowledge management system into the business processes at Swisscom AG – REST API definition
- Project manager, consultant, and sparring partner for the realignment/process digitalization at GIB Solutions AG
- Process designer and prototype for an AI-based real estate marketing system in Dubai
- Interim head of the ICT department at a telecom company, reorganizing and optimizing processes with a team of 5 at GIB Solutions AG
- Agile requirements engineer / external PO for a web-based solution for the German company DEHN AG
- Project management and consulting for the existing marketing and campaign planning solution at Swisscom AG
- Building the ALoHA nearshore offering at devpoint
Fatima D.
Last position:
Clinical Data Manager at Consultant – Clinical Data Management & Clinical Operations
- Served as a DM contractor for Mirum Pharmaceuticals between 2025-02-01 and 2026-05-31, leading end-to-end clinical data management activities
- Coordinated a significant networking event for HEMEX (Swiss CRO), fostering connections within the Swiss biotech ecosystem
- Engaged with stakeholders to explore innovative models that simplify execution and reduce operational burdens for clinical trials
Dariusz K.
Last position:
Business System Analyst at Zurich Insurance
Participating in a strategic enterprise project to introduce a centralized customer data platform ("Single Source of Truth") to eliminate redundant data storage and accelerate digital services
Analyzing and documenting business and system requirements for migrating large, heterogeneous data sets (ETL) and for continuous data synchronization between core systems and the new platform
Close collaboration with business units, data engineers and architects to gather and validate requirements, and to ensure data quality, consistency and regulatory compliance
Defining the migration strategy, specifying ETL processes and synchronization mechanisms, and documenting technical interfaces
Developing and executing test cases for migration and synchronization processes, and performing defect analysis to ensure data integrity and system stability
Technologies: SQL, Microsoft SQL Server, Azure DevOps, Confluence, UML, RESTful Services, Swagger, Postman
Kalin S.
Last position:
Sr Data Engineer / Architect at Samsung Logistics
- Architected and implemented a structured three-layer enterprise data warehouse model in Azure, establishing a robust and scalable data environment.
- Migrated legacy stored procedures to streamlined Azure Data Factory (ADF) pipelines, enhancing data processing efficiency.
- Introduced comprehensive Git-based source control, ensuring rigorous version management and collaborative development practices.
- Established automated data quality frameworks with proactive monitoring and alerting, significantly improving data integrity and reliability.
- Spearheaded the design of an enterprise data model, enabling a self-service BI environment that empowered business teams with advanced analytics capabilities.
- Developed and delivered insightful dashboards and reports in Power BI, transforming raw data into actionable business insights.
- Technologies: Azure Data Factory (ADF), Azure, MS-SQL, DataVault 2.0, Git, Power BI, data quality automation, Agile/Scrum, data modeling, self-service BI, stakeholder management.
André S.
Last position:
CEO at Cybo.Tech Advisory
Discover over 15,000 top freelancers
Statistics of experts using Data Quality
Aggregated from the professional profiles of matched freelancers.
Experience
22 years
Position duration
2.9 years
Positions per freelancer
11
Top business areas
Information Technology, Project Management, Quality Assurance
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Project Management, Finance
Bachelor's degree or higher
92%
Master's degree or higher
85%
Doctorate
15%
Certifications per freelancer
3
Most common languages
English, German, 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 Switzerland 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 Switzerland 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 19 Sep 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.
- Information Technology (70%)
- Professional Services (70%)
- Banking and Finance (55%)
- Manufacturing (45%)
- Healthcare (40%)
- Energy (30%)
- Government and Administration (30%)
- Education (25%)
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. It covers the rules, checks and operating processes that keep information trustworthy across business systems. Experts turn unclear data problems into measurable controls and practical remediation work.
Where it is used
Companies apply Data Quality practices wherever decisions, transactions or customer interactions depend on dependable information.
- Customer and supplier master data across CRM and ERP systems
- Product, location and reference data for commerce and operations
- Reporting, analytics and machine learning data preparation
- Data migration, consolidation and warehouse implementation
- Regulatory, finance and risk reporting processes
Ecosystem and tooling
The work connects data profiling and observability tools with databases, pipelines and business applications. Specialists may work with SQL, Python, cloud warehouses, ETL and ELT workflows, data catalogs, lineage tools and validation frameworks. They also translate business definitions into reusable quality rules and monitoring checks.
When companies need specialists
Freelance expertise is useful when internal teams see recurring duplicates, missing fields, conflicting definitions or unreliable reports. It also helps during acquisitions, system replacements, migrations and new analytics initiatives. In Switzerland, remote collaboration can work well when documentation and ownership are clear, while on-site workshops may help align business and technical teams across languages.
- Profile critical datasets and identify root causes
- Define quality dimensions, thresholds and exception workflows
- Clean, match and enrich records without losing traceability
- Establish monitoring, ownership and continuous improvement
What strong professionals deliver
Strong professionals combine analytical depth with knowledge of business processes. They distinguish a source-system defect from a transformation issue and prioritize remediation by business impact. Their deliverables can include a data quality assessment, rule catalog, matching logic, issue backlog, dashboards and an operating model that teams can maintain.
Choosing the right fit
Look for evidence of work with the systems, data domains and delivery model relevant to your project. Ask how the specialist measures accuracy, handles exceptions, protects sensitive information and proves that fixes remain effective downstream. The best fit communicates clearly with data owners, application teams and leadership, and leaves behind documented rules rather than one-off cleanup scripts.
Frequently asked questions
Questions about Data Quality? Start with the answers below.
Data Quality is used to assess and improve whether information is accurate, complete, consistent, timely and suitable for a business purpose. Companies rely on it for master data, reporting, migrations, analytics, customer operations and risk processes.
Data Quality focuses on the condition and usability of data, while data governance defines ownership, policies and decision rights. Data observability focuses on detecting changes and failures across pipelines and systems. The practices overlap, but they answer different operational questions.
A strong Data Quality specialist often combines SQL, data profiling, ETL or ELT knowledge and database experience with data modeling and metadata management. Skills in data governance, master data management, cloud warehouses and business process analysis are also valuable.
The right level depends on the scope, data complexity and consequences of errors. Data Quality work on one dataset may need a focused specialist, while an enterprise program benefits from someone who can shape rules, ownership, tooling and change processes across several domains.
Yes, Data Quality work is often suitable for remote delivery because profiling, rule design and monitoring can be performed through secure access and shared documentation. On-site sessions can still be useful for workshops with business owners, especially when teams work across German, French, Italian or English.
Ask for concrete examples of profiling, root-cause analysis, remediation and monitoring rather than broad tool lists. A capable Data Quality professional explains how rules were defined, how exceptions were handled and how the business confirmed that the data became more useful.
Data Quality projects may involve SQL and Python, data warehouses, ETL or ELT tools, data catalogs, lineage systems and dedicated profiling or observability products. The tool choice should follow the data landscape, controls required and skills available to maintain the solution.
A Data Quality freelancer may deliver a current-state assessment, quality rule catalog, profiling results, matching logic, remediation plan and monitoring design. They should also document definitions, ownership, exceptions and handover steps so internal teams can operate the controls after the engagement.
The average hourly rate of freelancers in Switzerland who have used Data Quality in their recent projects is 135 €, which corresponds to a daily rate of about 1,080 € based on an 8-hour working day.
Of the freelancers in Switzerland who have used Data Quality in their recent projects, 92% hold at least a Bachelor's degree, 85% hold at least a Master's degree, and 15% hold a doctorate.
On average, freelancers in Switzerland who have used Data Quality in their recent projects have 22 years of professional experience, with a single engagement typically lasting around 2.9 years.
The most common languages among freelancers in Switzerland who have used Data Quality in their recent projects are English (100%), German (90%), and French (40%).
The most common industries among freelancers in Switzerland who have used Data Quality in their recent projects are Information Technology (70%), Professional Services (70%), and Banking and Finance (55%).
The most common business areas among freelancers in Switzerland who have used Data Quality in their recent projects are Information Technology (80%), Project Management (80%), and Quality Assurance (75%).
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.
Zurich Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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Philipp Thomaschewski
FRATCH CEO
