Data Quality Experts in Nuremberg
matched in minutes with vetted, available freelancersHire experts who define data quality rules, build validation pipelines and resolve duplicate or incomplete records across CRM, ERP and analytics systems. FRATCH connects you with precise AI-matched, vetted and available freelancers for focused data quality work.
Meet FRATCH Experts in Nuremberg, who have recently used Data Quality
Bhagyashree M.
Last position:
Salesforce Administrator at gkk Frankfurt GmbH
- Translated complex operational requirements into scalable Salesforce configurations, automation flows and governance policies, ensuring clean and maintainable implementations
- Designed and optimised Flows to eliminate manual steps in key business processes, improving both performance and process compliance
- Managed user roles, permission sets and security settings for a multi-team Salesforce org; ensured data quality and system stability through structured governance practices
- Supported Marketing Cloud integrations and campaign automation workflows, collaborating with business teams on data-driven audience segmentation
- Coordinated release management and deployment activities with development teams, contributing to structured change control processes
Tobias V.
Last position:
Managing Partner at Unwritten GmbH
- Pioneering work in personalized AI: developing a framework for “Interactive Content” (RAG) for novels, lectures, expert debriefing
- Successful launch of Einbug, the Pantopia chatbot, with media coverage (SZ interview)
- Creating compelling AI personalities: AI blog ([link] 100% personalized learning environments, Perry Rhodan, among others.
Elnazossadat H.
Last position:
Data Analyst at Siemens Healthineers
- Developed KPI dashboards using Power BI and DAX for 4+ business units, improving reporting transparency and strategic decision support.
- Migrated enterprise finance data views into dbt models, implementing modular SQL transformations, version-controlled data pipelines, and automated documentation to create a scalable analytics layer.
- Built dimensional data models in Snowflake for enterprise finance data, enabling scalable forecasting and supporting executive decision-making.
- Designed end-to-end ETL/ELT pipelines using Snowflake and SAP HANA, integrating data from 3+ enterprise systems.
- Automated monthly reporting workflows using SQL and Power BI, delivering strong business impact by reducing manual effort by 80%.
- Collaborated with finance stakeholders to translate business requirements into analytical data models, supporting strategic decision-making cycles.
- Delivered ad-hoc financial reports using Power BI, reducing turnaround time by 60%.
- Implemented data validation logic in SQL, resolving 95% of recurring data quality issues.
Imane H.
Last position:
Assistant Manager People insights/Intelligence at adidas HQ
- Collected, analysed, and interpreted HR data from multiple systems
- Conducted ad-hoc people data analyses for stakeholders
- Supported Employee Listening and ensured actionable survey insights
- Built intuitive dashboards and visualizations in SuccessFactors, PowerBI, and Qualtrics
- Produced regular reports and dashboards on key HR metrics
- Contributed to people analytics projects as a junior team member
- Collaborated with HR Tech and Data teams to improve data quality
- Ensured ethical and governed data use with Legal, Data Privacy, Labour Relations and Works Council
Benjamin S.
Last position:
CRM strategy & requirements analysis for marketing campaigns in the automotive sector at AUDI AG
- Development of strategies, processes and system requirements to further develop the lead and campaign streams of a Salesforce system for the subsystems Sales Cloud, Marketing Cloud and Analytics Cloud
- Gathering and creation of marketing strategy concepts for direct sales, focusing on lead generation for new and existing customers
- Analysis and optimization of existing and new contact points
- Derivation of system requirements and user tests for new developments
- Establishment of a requirements and implementation process for business needs at the interface between CRM strategy and marketing system operations
- Facilitation of ideation workshops with the project's stakeholders
- Mediation between business and technical project stakeholders
- Analysis and post-documentation of existing marketing strategies and the system functions already created for them
- Analysis of target groups and pre-system data quality as a foundation for new CRM strategies
- Consultation on content and asset strategy for marketing campaigns
- Definition of KPIs and other performance criteria for the system and CRM strategy
Felix K.
Last position:
Senior Data Scientist at Novartis Pharma AG
- Led the implementation and validation of digital technology for real-world mobility assessment across clinical trials with high compliance rates
- Headed a cross-functional initiative that bridged clinical and data science teams, aligning digital technology integration with strategic goals
- Innovated algorithm development for sensor data analysis, leveraging time-series data to extract novel insights and improve predictive accuracy
- Designed and deployed predictive models using machine learning, integrating digital device data with clinical datasets
- Delivered strategic insights through the creation of dashboards and reports, ensuring effective data quality control and visualization for clinical trials
- Ensured reproducibility in data science workflows by establishing robust coding practices, comprehensive documentation, and version control
- Co-led exploratory statistical plans for digital biomarkers, advancing understanding and application of digital technologies in healthcare research
- Advised clinical teams as a subject-matter expert on digital technologies, fostering strategic integration and effective utilization in clinical trials
- Managed stakeholder engagement by collaborating with internal and external stakeholders, including contract research organizations and technology vendors
- Influenced decision-making by presenting analyses and findings to various management levels and stakeholders, emphasizing actionable insights and implications
- Disseminated knowledge through peer-reviewed publications
Andreas B.
Last position:
Interim Manager - Project Excellence & Transformation at Brachwitz Interim Management
- Structured digitalization mandates for project businesses, developing governance frameworks, data models, and digital toolchain integration strategies for complex industrial environments
- Advised on data break resolution, standardized data flows, and end-to-end process harmonization across project management chains
- Developed knowledge retention strategies and digital tools to systematically capture and share organizational expertise
- Achieved active market positioning for project excellence and digitalization mandates in industrial environments (Siemens Energy, EFESO, Capgemini Engineering)
Discover over 15,000 top freelancers
Statistics of experts using Data Quality
Aggregated from the professional profiles of matched freelancers.
Experience
14 years (Germany: 16 years)
Position duration
3.5 years (Germany: 3 years)
Positions per freelancer
7 (Germany: 10)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Automotive, Professional Services
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
100% (Germany: 94%)
Master's degree or higher
83% (Germany: 67%)
Doctorate
17% (Germany: 10%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 98%)
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 Nuremberg 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 Nuremberg 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.
- Information Technology (71%)
- Automotive (43%)
- Professional Services (43%)
- Energy (29%)
- Healthcare (29%)
- Advertising (14%)
- Education (14%)
- Fashion (14%)
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, valid and fit for its intended use. Specialists examine how information is captured, transformed, stored and consumed across business systems. The work combines analysis, rules, process design and reliable measurement rather than simple spreadsheet cleanup.
Systems and Deliverables
Data quality work appears in customer master data, product catalogs, finance records, supply chains, reporting layers and machine learning inputs. Typical deliverables include:
- Data profiling and quality assessments
- Validation rules and monitoring dashboards
- Deduplication and standardization pipelines
- Remediation workflows and ownership models
Ecosystem and Skills
Professionals may work with SQL, Python, dbt, Apache Airflow, Great Expectations, Soda, Talend, Informatica, Microsoft Purview or cloud data warehouses. Strong results also require knowledge of ETL and ELT design, metadata, APIs, master data management and data governance. The right toolkit depends on where errors enter the data flow and how teams use the output.
When Companies Need Specialists
Companies often bring in freelance expertise when a migration exposes inconsistent records, dashboards lose trust or a new integration changes data structures. Nuremberg businesses may need support across manufacturing, logistics, healthcare, services and commerce, with remote delivery or on-site collaboration depending on access and stakeholder needs. Useful signals include:
- Repeated reconciliation work between systems
- Conflicting customer or product records
- Quality issues delaying reporting or automation
What Strong Experts Do
A strong specialist connects technical checks with business meaning. They define rules with data owners, trace defects to their source, distinguish harmless variation from harmful error and document decisions clearly. They also design controls that run continuously, explain exceptions to non-technical teams and leave maintainable processes behind.
Choosing the Right Fit
Assess a professional by asking for examples of profiling, root-cause analysis, remediation and quality monitoring in systems similar to yours. Discuss source systems, data volumes without relying on headline metrics, sensitive access requirements, ownership and success criteria before work begins. For Nuremberg teams, clarify German or English communication needs and whether workshops require local presence.
Frequently asked questions
Before you brief your next project: the most common questions about Data Quality.
Data Quality is used to make information accurate, complete, consistent, valid and usable for operations, reporting and automation. Specialists profile records, define controls, correct defects and monitor quality as data moves between systems.
Data Quality covers the wider system of rules, measurement, ownership and ongoing improvement. Data cleansing is one part of that work, focused on correcting, standardizing or removing problematic records.
A strong Data Quality freelancer usually understands SQL, Python, ETL or ELT pipelines, data modeling and cloud warehouses. Experience with master data management, metadata, data governance and tools such as Great Expectations or Soda can also be valuable.
The right level of Data Quality experience depends on the systems, risk and scope of the assignment. A focused profiling task may need a specialist who can work independently with one data source, while cross-system remediation requires experience with ownership, migrations and change management.
Data Quality work is often suitable for remote collaboration because profiling, rule design and monitoring can be performed through secured environments. On-site workshops in Nuremberg can still help when specialists must map operational processes or align several data owners.
A Data Quality specialist is useful when errors repeat across systems, teams disagree about definitions or reporting cannot be trusted. Analysts can identify visible issues, while a specialist typically traces root causes and creates controls that prevent the same defects from returning.
Ask how the Data Quality professional would profile your sources, prioritize defects and prove that remediation worked. Look for clear reasoning, practical rule design, documented assumptions and an approach that includes data owners rather than treating quality as a purely technical task.
Before starting Data Quality work, clarify source systems, access permissions, business definitions, ownership, sensitive fields and the expected deliverables. Agree on how defects will be prioritized and how ongoing monitoring will be maintained after the engagement ends.
The average hourly rate of freelancers in Nuremberg, Germany who have used Data Quality in their recent projects is 93 €, which corresponds to a daily rate of about 743 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Data Quality in their recent projects, 100% hold at least a Bachelor's degree, 83% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Nuremberg, Germany who have used Data Quality in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 3.5 years.
The most common languages among freelancers in Nuremberg, Germany who have used Data Quality in their recent projects are German (100%), English (100%), and French (43%).
The most common industries among freelancers in Nuremberg, Germany who have used Data Quality in their recent projects are Information Technology (71%), Automotive (43%), and Professional Services (43%).
The most common business areas among freelancers in Nuremberg, Germany who have used Data Quality in their recent projects are Business Intelligence (86%), Information Technology (86%), and Product Development (86%).
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.
Berlin 
Hamburg 
Munich 
Cologne 
Frankfurt 
Stuttgart 
Dusseldorf 
Hanover Request a free demo
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FRATCH CEO
