Data Quality Experts in Stuttgart
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Meet FRATCH Experts in Stuttgart, who have recently used Data Quality
Talha Erciyes
Last position:
Interim Senior Finance Business Partner at SharkNinja Europe Ltd.
Responsibility for commercial finance in Central Europe (DACH and Poland), reporting to the EMEA Commercial Finance Director. Monthly financial reporting, forecasting, and variance analysis, evaluation of promotions and special campaigns, management of planning processes including budgeting, as well as preparation of QBR materials up to CFO level. Took over functional leadership in the finance team after the mandate holder was unavailable.
Francis Wambugu
Last position:
German Teacher at Goethe Institut-Nairobi
- Teaching German literature and linguistics
Robert Wieland
Last position:
Data Architecture Manager at Accenture
- Data Migration Engine / Data Migration from proprietary source systems to SAP/S4 (SAP S/4 HANA Migration cont.)
- Development data authorization Concept
- Conception of system architecture / data architecture / data integration – continuous extensions
- Development conceptional / logical (MDM) data Model - continuous extensions
Mark Wieczorrek
Last position:
Manager & Product Owner Sustainability (ESG) at EGC Eurogroup Consulting AG
- Designing, consulting, and managing strategic transformation projects for banks, insurers, and financial associations with a focus on efficiency, digitalization, and ESG
- Owning market positioning in sustainability through professional publications, whitepapers, and presentations at the top management level
- Developing and executing targeted acquisition strategies for ESG transformation projects and the insurance market, including identifying market opportunities and creating proposals in collaboration with executive management
Katherina Schock
Last position:
Team Lead Instore Logistics Management at Breuninger GmbH & Co
Led the central Instore Logistics Team and oversaw support operations across 13 stores in Germany and Luxembourg, ensuring seamless coordination of logistics processes and strategic direction.
Oversaw all merchandise management processes across stores, eCommerce, and Pick from Store, ensuring alignment, efficiency, and operational consistency.
Analyzed staffing procedures and personnel costs across support teams, providing data-driven recommendations to the Executive Board for annual budget planning.
Led continuous improvement initiatives including documentation, KPI development, and performance tracking to drive operational excellence through data-based insights.
Provided technical support for new store openings and transformation projects, ensuring integration with central logistics and adherence to EU Price Indication Regulation (PAngV).
Managed optimization and digitalization projects, including piloting digital price tags across stores to enhance efficiency and customer experience.
Hussam Greg
Last position:
Consultant at Insurance company
- Conducting gap analyses and optimizing the documented framework
- Adapting templates for identification, risk analysis, and due diligence
- Supporting departments in conducting risk analyses
- Tracking results and ensuring data quality
- Enhancing and optimizing the Outsourcing Control Report (OCR) as a management and monitoring tool
- Developing and introducing an automated concept for concentration risk
- Conducting a gap analysis on DORA regarding regulatory requirements
Vladimir Grega
Last position:
Design Engineer (freelance) at BITZER Kühlmaschinenbau GmbH
- As part of the development of a new series of screw compressors, with a special focus on the design of a new electrical terminal box:
- Taking over the analysis of the design requirements and the relevant documents as well as CAD data
- Developing a well-thought-out concept for the design of the electrical terminal box
- Considering technical, economic, and safety-related requirements
- Compliance with safety regulations and IP protection requirements
- Taking into account design guidelines as well as assembly and user-friendliness
- Considering UL certification, plastic injection-mold-friendly design with Siemens NX, supplier requirements, cost-effectiveness, and scalability for the entire series
- Subsequent precise and targeted implementation of the design based on the developed concept
Divij Wadhawan
Last position:
Data Scientist at Daimler R&D, Daimler AG
- Mercedes Me is an app that connects your phone to several features in the car
- Implemented analytical KPIs for the Digital Drivers Log (Fahrtenbuch) feature
- Used PySpark on Databricks
Discover over 15,000 top freelancers
Statistics of experts using Data Quality
Aggregated from the professional profiles of matched freelancers.
Experience
13 years (Germany: 16 years)
Position duration
1.3 years (Germany: 3 years)
Positions per freelancer
11 (Germany: 10)
Top business areas
Project Management, Information Technology, Operations
Top industries
Professional Services, Banking and Finance, Insurance
Certification focus areas
Information Technology, Quality Assurance, Business Intelligence
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
50% (Germany: 68%)
Certifications per freelancer
4 (Germany: 3)
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 98%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Stuttgart 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 Stuttgart 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it covers
Data quality is the discipline of making data fit for use. It focuses on accuracy, completeness, consistency, timeliness, and uniqueness across operational and analytical systems. Strong work in this area reduces broken reports, failed automations, and duplicate records.
Typical work
- Data profiling and rule design
- Cleansing, standardization, and deduplication
- Validation checks in ETL and ELT flows
- Master data and reference data controls
- Monitoring, alerts, and issue triage
Tools and stack
Experts often work with SQL, Python, dbt, Great Expectations, Soda, Informatica, Talend, and cloud warehouse tools. They also connect quality checks to pipelines, orchestration, and catalog or lineage tools so issues are found early and tracked clearly.
When to bring in help
Companies bring in freelance specialists when data starts drifting across sources, migrations are underway, or reporting needs tighter control. In Stuttgart, this often matters for manufacturing, mobility, finance, and supply-chain teams that rely on clean master data and stable reporting.
What strong specialists do
Good professionals do more than write checks. They define practical rules with business owners, trace defects to the source, and set up monitoring that teams can maintain. They balance strict controls with workflows that do not slow delivery.
Why it matters
Poor data quality spreads fast. It affects analytics, customer records, product data, and compliance evidence. Strong data quality work creates trust in dashboards, reduces manual correction, and makes downstream systems more reliable.
Frequently asked questions
Key details about Data Quality, drawn from the questions we get asked most.
A strong Data Quality specialist finds where data breaks down and puts controls in place to stop it. That can include profiling, validation rules, deduplication, and monitoring across source systems, warehouses, and reporting layers.
Data Quality focuses on whether the data is fit for use, while governance defines ownership, rules, and accountability. Data engineering moves and transforms data; quality work adds checks, thresholds, and remediation so the pipeline delivers trusted results.
A Data Quality freelancer often uses SQL, Python, dbt, Great Expectations, Soda, or tools such as Informatica and Talend. The right stack depends on whether the project sits in batch pipelines, cloud warehouses, or operational systems.
A strong Data Quality professional usually knows data modeling, ETL or ELT design, source-to-target analysis, and basic analytics. Communication matters too, because many fixes require agreement on definitions with business and data owners.
A Data Quality project can be small if it only needs a few rules and checks, or larger if it involves many systems and business domains. The key is not years on paper, but whether the specialist has handled profiling, remediation, and sustainable monitoring before.
Yes, most Data Quality work can be done remotely because it relies on access to data, queries, pipelines, and clear communication. On-site time can help when teams need faster alignment on business definitions, especially in Stuttgart-based operations and transformation projects.
Look for clear examples of how the Data Quality specialist found the root cause, not just the symptom. Good signs are practical rules, explainable checks, documentation that others can use, and remediation steps that stay in place after handover.
No, Data Quality is broader. Data profiling helps you understand the data, and data cleansing fixes issues such as duplicates or bad formats, but quality work also includes prevention, monitoring, and governance around the rules.
The average hourly rate of freelancers in Stuttgart, Germany who have used Data Quality in their recent projects is 99 €, which corresponds to a daily rate of about 794 € based on an 8-hour working day.
Of the freelancers in Stuttgart, Germany who have used Data Quality in their recent projects, 100% hold at least a Bachelor's degree and 50% hold at least a Master's degree.
On average, freelancers in Stuttgart, Germany who have used Data Quality in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 1.3 years.
The most common languages among freelancers in Stuttgart, Germany who have used Data Quality in their recent projects are German (100%), English (100%), and Spanish (25%).
The most common industries among freelancers in Stuttgart, Germany who have used Data Quality in their recent projects are Professional Services (63%), Banking and Finance (50%), and Insurance (50%).
The most common business areas among freelancers in Stuttgart, Germany who have used Data Quality in their recent projects are Project Management (88%), Information Technology (63%), and Operations (63%).
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.
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