Data Quality Experts in Cologne
with precise AI matching from over 15,000 CVsHire experts who improve data validation, profiling and governance across business systems. Work with vetted, available freelancers matched quickly to your requirements, whether you need a focused quality assessment or support for a lasting data management program.
Meet FRATCH Experts in Cologne, who have recently used Data Quality
Hooman B.
Last position:
Fullstack Developer at Möbel Roller GmbH
- Further development of the existing e-commerce platform based on SAP Commerce (Hybris) to meet the growing demands of digital commerce.
- Ensuring the scalability and performance of the backend, so the platform remained stable and efficient even under heavy user load.
- Development and integration of new OCC REST APIs and services for modular extensions and flexible adjustments, to implement new features quickly.
- Optimization of data flows and interfaces, which significantly improved platform efficiency and system performance.
- Ensuring a maintainable and scalable code base by using Clean Code principles, proven design patterns, and a future-proof architecture.
- Reduction of errors through extensive testing with JUnit, Mockito, and load tests with Gatling, supported by the introduction of automated test processes.
- Improved system performance through targeted refactoring measures and efficient database queries, especially to handle peak loads.
- Use of modern cloud and monitoring tools such as Kubernetes, Google Cloud Platform (GCP), and Grafana to ensure a stable and monitored infrastructure.
- Clear improvement in efficiency, scalability, and reliability of the platform, which now meets the demands of a dynamic and growing e-commerce market.
Loretta A.
Last position:
Master Thesis Student at Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Future Fuels
- Managed end-to-end data workflows for LCA and carbon footprint assessments, including data collection, validation, structuring, and LCI modeling for metal alloys, ensuring high data quality and traceability.
- Developed a basic Excel automation tool to simplify carbon footprint calculations of metal alloys, replacing repetitive modelling in the software that previously took several hours.
- Communicated environmental impact results through quantitative analysis, visualizations and reports to support the broader project strategy.
- Performed environmental hotspot and scenario analysis to identify key impact drivers and assess opportunities for emissions reduction.
Henning U.
Last position:
Senior Expert Data Governance, Master Data Quality and Data Migration at E.ON
- Planning and implementation of a migration strategy for master and transaction data for the continuous loading of a cloud-independent database
- Creation and pilot implementation of a company-wide Business Data Model for customers, suppliers, contracts, products, prices, consumption, invoices, and dunning
- Concept and consulting for a Data Governance Framework incl. definition of committees, roles, processes, and metadata model
- Operationalization of the Data Governance Framework with definition of data standards
- Sub-project management in two pilot projects (PoCs) for Data Governance systems (ErwinDIS and Atlan)
- Training and coaching the data team in migration, data quality, and data modeling
Markus B.
Last position:
Consultant, Technical Project Manager at Lanxess
- Project: ESU Windows and SQL Server consolidation / Configuration Management in ServiceNow
- Creation of an as-is analysis of all servers worldwide
- Creation of an as-is analysis of all SQL servers worldwide
- Creation of requirements analyses for SQL and server migrations
- Coordination of requirements with partners for migrations to Hyper-V (on-premises) or Azure Cloud
- Moderation of jour fixe meetings
- Creation of roadmaps and solution models for server migrations
- Setup of test scenarios
- Moderation of workshops for the introduction of a Global Admin Team
- Creation of data models (CMDB) in ServiceNow
- Conducting workshops for the CMDB data model
- Creation of solution models for the CMDB
- Creation of seamless configuration and work documentation for the CMDB
- Creation of reports for license management
- Creation of KPIs for data quality in ServiceNow
- Creation of a service catalog
- Moderation of workshops for creating service requests
- Interface between needs analysis and ServiceNow development team
- Systems used: Windows 7, Windows 10, Microsoft Office 365/2010, Windows Server 20xx, SQL Server 20xx, SharePoint, Azure Cloud, Hyper-V, ServiceNow, various tools
Alexander B.
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
Nenad B.
Last position:
Safety Video Analytics Project for Airbus at Airbus
- Developed a real-time video analytics proof-of-concept for deployment on NVIDIA Jetson edge devices.
- Implemented DeepStream pipelines including object detection, tracking, human pose estimation, face anonymization, and zone intrusion detection.
- Built a Qt/Python demonstration UI interfacing with the AI pipeline via REST APIs.
Beshr A.
Last position:
System Administrator – HealthCare IT & Data Infrastructure at Cellitinnen Hospital Association
- Integration of medical modalities (including ultrasound) into the existing IT infrastructure (DICOM, HL7) – put into operation within the planned timeframe.
- Administration and optimization of PACS systems for efficient archiving and distribution of radiology image data across multiple locations.
- Ensuring consistent data quality and seamless interoperability in data exchange between HIS, RIS, and PACS.
- Close collaboration with medical staff to analyze and digitally optimize clinical workflows.
- Requirements management and test coordination when implementing clinical requirements in complex IT structures.
Dr Stefan N.
Last position:
Independent Consultant
- Intended break
- Lecturing at universities
- Mentoring
- Social engagement
- Coaching education
- Founding of research institute “Center For Impactful Organization Design (CIOD)”
Johannes W.
Last position:
Senior Data Engineer at Soorce GmbH
- Analysis of business requirements
- Integration of different data sources such as ERP systems, production systems, and external data sources
- Implementation of load processes and processing logic with MSSQL
- Data modeling and optimization of data models
- Setting up data quality management incl. data profiling with dynamic programming
- Support in designing and establishing data governance, especially in the areas of data quality management and data protection
- Support in developing BI solutions with Tableau to help decision-making processes
Rüdiger T.
Last position:
Finance Director at PSG Germany GmbH, a Dover company
B2B pumps for chemicals, life sciences, semiconductors etc. Stabilization and optimization of the finance function, closing / budgeting / reporting / audits / SOX / PMI
Rodion O.
Last position:
Founder, CTO & Managing Director at MYNR Product Mining GmbH
- Responsible for the architecture and development of an AI-native SaaS platform for industrial product portfolio management.
- Designed the modern data platform architecture on Azure for scalable analytics and enterprise data integration.
- Built enterprise data ingestion and transformation pipelines across complex industrial system landscapes.
- Developed graph-based representations of product structures and dependencies for analytical reasoning.
- Designed and implemented an agentic AI framework for AI-supported decision workflows.
- Built scalable analytical microservices and integrated reporting through modern BI technologies.
- Coordinated backend, AI, and frontend development across the MYNR platform stack.
Michael W.
Last position:
Founder & Salesforce Consultant at MW Cloud Solutions (MWCS)
- End-to-end implementations of Marketing Cloud Next (Growth/Advanced), from discovery workshop to go-live — Data 360 (Data Cloud) setup, data streams and mapping, identity resolution rules (match & reconciliation), consent management, Sales Cloud integration.
- Campaign orchestration across the MCN flow types — segment-, event-(forms & engagement), schedule- and record-triggered flows (Salesforce & Data Cloud) plus API-based on-demand sends; segmentation and activation with Data Graphs, Calculated Insights, and Einstein personalization.
- Multilingual email template systems with dynamic, personalized content; deliverability (SPF/DKIM/DMARC) and GDPR-compliant double opt-in journeys.
- Operational support for Marketing Cloud Next orgs in ongoing consulting projects — campaign operations, data quality, performance analysis, and release readiness: campaigns deliver on schedule, credit costs stay predictable.
- At the same time, Account Engagement (Pardot) client projects — audits, implementations, lead scoring & grading; AE-MCN migration assessments; Agentforce grounding and guardrails.
Stanislav S.
Last position:
Interim CTO / IT Consultant (Cloud & App Security · AI & Web3) at Deutsche Bank Group; Startups
- Spearheaded strategic and operational oversight of IT infrastructures to accelerate innovation and ensure audit-proof delivery.
- Acted as key liaison between management, business departments, and engineering, actively engaging in coding, cloud architecture, and CI/CD to resolve critical path challenges.
- Engineered and implemented an AI Governance Program to manage risks and ensure compliance with the EU AI Act, reducing AI use-case approval times from 8 to 3 weeks.
- Delivered and deployed secure AI systems into production (RAG-based knowledge platforms), resulting in a 35% decrease in standard support ticket volume.
- Established robust security standards and governance frameworks for APIs (OAuth2/OIDC, mTLS) and cloud platforms (AWS/GCP) to guarantee compliance and system integrity.
- Hardened cloud infrastructure by implementing Zero Trust principles and a comprehensive observability stack (logging/alerting), achieving 99.9% availability in a 24/7 on-call environment.
Alexander V.
Last position:
Senior DevOps / Platform Engineer at Kaufland e-commerce / real.digital (ex hitmeister.de)
- Evolved the platform from bare-metal infrastructure with a monolithic PHP application to a hybrid Google Cloud architecture with Go microservices on Kubernetes
- Managed and scaled a production infrastructure with 300+ VMs and dozens of clusters, including MySQL, PostgreSQL, MongoDB, RabbitMQ, Redis and Elasticsearch clusters
- Designed architecture, deployment, monitoring, performance analysis, and upgrades for all platform services using Terraform and Ansible
- Migrated observability systems from ELK and Prometheus to Datadog, managed with Terraform
- Introduced Jenkins CI/CD with SonarQube integration and automated tests to speed up feedback cycles
- Containerized the testing environment and implemented GitLab CI pipelines for Docker image builds, static code analysis, and infrastructure tests
- Performed zero-downtime migrations of MySQL and MongoDB clusters to Google Cloud
- Developed reusable Ansible roles for database clusters and automated data obfuscation for staging environments
- Decomposed monolithic databases and migrated to microservice architectures
- Built tools to detect and optimize slow queries in MySQL and MongoDB
- Conducted online schema migrations with pt-online-schema-change without downtime windows
- Developed internal Go applications for batch queries, GitLab-Jira integration, and MongoDB backup recovery
- Technologies: Debian, Ubuntu, Alpine, Go, Bash, Python, PHP, SQL, GitLab CI, Jenkins, Drone CI, MySQL, MongoDB, PostgreSQL, Redis, Elasticsearch, RabbitMQ, Kafka, Docker, Kubernetes, Nomad, Ansible, Terraform, Grafana, ELK, Prometheus, Datadog, Nagios, Zabbix, Nginx, HAProxy, Vault, Helm, SonarQube, Filebeat, Auditbeat, Google Cloud, AWS
Michael T.
Last position:
B2B Growth Consultant at Loy & Co. Corporate Finance GmbH
Optimization of inbound and outbound processes for lead generation for B2B sales with a focus on prospect data for the software and IT target group
Setting up a structured cold e-mail marketing program for B2B lead generation in the German mid-sized market
Derivation of various optimization measures for inbound growth processes (website, SEO)
Generation of a double-digit number of leads from mid-sized companies through cold e-mail campaigns
Optimization of the CRM system Pipedrive for structured growth campaigns
Discover over 15,000 top freelancers
Statistics of experts using Data Quality
Aggregated from the professional profiles of matched freelancers.
Experience
18 years (Germany: 16 years)
Position duration
1.9 years (Germany: 3 years)
Positions per freelancer
11 (Germany: 10)
Top business areas
Information Technology, Business Intelligence, Quality Assurance
Top industries
Information Technology, Professional Services, Manufacturing
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
94% (Germany: 95%)
Master's degree or higher
78% (Germany: 68%)
Doctorate
11%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 98%)
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 Cologne 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 Cologne 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 (75%)
- Professional Services (55%)
- Manufacturing (50%)
- Banking and Finance (40%)
- Retail (40%)
- Automotive (35%)
- Transportation (35%)
- Education (30%)
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 combines profiling, validation, cleansing, enrichment and ongoing monitoring across databases, files, APIs and business applications. Data quality management turns unclear records into trusted information for operations, reporting and analytics.
Where it is used
Companies apply data quality practices wherever unreliable records create operational or regulatory risk:
- Customer and supplier master data
- Product, location and reference data
- Migration into ERP, CRM or cloud platforms
- Data warehouses, lakehouses and reporting layers
- Matching, deduplication and address standardisation
Strong quality controls help teams reduce duplicate entities, detect missing values and trace changes back to their source. They also make downstream automation and decision-making more dependable.
Ecosystem and tooling
A Data Quality specialist may work with SQL, Python, spreadsheets and database controls, alongside data catalogues, lineage tools and observability products. Depending on the landscape, the work connects with ETL and ELT pipelines, APIs, cloud storage, CRM and ERP platforms. Knowledge of data governance, metadata, reference data and master data management is often essential.
When companies need support
Freelance expertise is useful when internal teams lack the time or neutral perspective to investigate recurring data problems. Typical assignments include defining quality rules, assessing source systems, preparing migration data and introducing monitoring. In Cologne, specialists may work remotely or on site with teams across business, IT and compliance, with German or English collaboration depending on the organisation.
What the work delivers
A well-scoped engagement should produce more than a one-time clean-up. Expected deliverables can include a data profile, issue catalogue, rule set, ownership model, remediation workflow and quality dashboard. The specialist should connect each rule to a business purpose and document exceptions so that teams can maintain the result after handover.
Signs of strong expertise
Look for professionals who can explain quality problems in business terms and verify findings at source rather than masking symptoms. Relevant evidence includes:
- Clear profiling methods and reproducible validation rules
- Experience with entity resolution and deduplication
- Practical knowledge of pipelines, APIs and databases
- Careful documentation of lineage, ownership and exceptions
- Measurable monitoring plans agreed with data users
The strongest specialists combine technical investigation with structured communication. They protect sensitive information, challenge ambiguous requirements and leave behind controls that fit everyday processes.
Frequently asked questions
Need clarity? These are the questions we hear most often about Data Quality.
Data Quality is used to check whether information is accurate, complete, consistent, timely and suitable for a business purpose. Specialists apply profiling, validation, cleansing and monitoring to customer, product, supplier, financial and operational data.
Data Quality focuses on the condition and usability of records, while data governance defines ownership, policies, standards and decision rights. The two areas work together: governance sets expectations, and quality controls show whether those expectations are being met.
A strong Data Quality specialist often works with SQL, Python, databases, ETL or ELT pipelines and data integration. Knowledge of master data management, metadata, lineage, data catalogues and business processes is also valuable.
The right level for a Data Quality project depends on its scope, data complexity and risk. A focused profiling task may need a specialist for a short engagement, while cross-system remediation requires someone who can design rules, coordinate owners and establish lasting monitoring.
Yes, Data Quality work is often suitable for remote collaboration because specialists can access documented extracts, schemas and profiling environments securely. On-site workshops in Cologne can still help when teams need to map processes, agree ownership or resolve conflicting business definitions.
Before engaging a Data Quality specialist, define the business process affected, the source systems involved and the decisions the data must support. Useful starting material includes sample records, known incidents, existing rules, access constraints and the expected handover.
Ask a Data Quality professional to explain how they would profile the data, prioritise issues and prove that a correction worked. Look for clear reasoning, practical validation rules, attention to lineage and ownership, and documentation that another team can maintain.
Data Quality projects depend on close communication between technical and business teams, so German or English may be appropriate depending on the organisation. Remote work can cover analysis and implementation, while workshops are useful for agreeing definitions, thresholds and responsibilities.
The average hourly rate of freelancers in Cologne, Germany who have used Data Quality in their recent projects is 108 €, which corresponds to a daily rate of about 863 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used Data Quality in their recent projects, 94% hold at least a Bachelor's degree, 78% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers in Cologne, Germany who have used Data Quality in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Cologne, Germany who have used Data Quality in their recent projects are German (100%), English (100%), and French (20%).
The most common industries among freelancers in Cologne, Germany who have used Data Quality in their recent projects are Information Technology (75%), Professional Services (55%), and Manufacturing (50%).
The most common business areas among freelancers in Cologne, Germany who have used Data Quality in their recent projects are Information Technology (90%), Business Intelligence (75%), and Quality Assurance (65%).
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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Hamburg 
Munich 
Frankfurt 
Stuttgart 
Dusseldorf 
Hanover 
Nuremberg Request a free demo
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FRATCH CEO
