Data Catalog Experts in Germany
in minutes with vetted, available specialists and the power of AIHire experts who design data catalogs, connect metadata sources, and improve data discovery across your stack. They support governance, lineage, glossary, and access workflows, with fast, precise matching to vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used Data Catalog
Philipp Grunert
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
- Implementation of automated end-to-end cloud processes
- Development of LLM and NLP models
- Creation of interactive reports
- Support for national and international large corporations as well as medium-sized companies in implementing ML projects
Serge Kalinin
Last position:
MLOps (machine learning operations) at REWE Digital GmbH
- It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
- GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
- Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
- CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
Jan Krol
Last position:
Data Expert at Manufacturing
Marcus Brandt
Last position:
Managing Director at Petermann Brandt GmbH
- Development and implementation of custom IT solutions for key customers.
- More than 15 years of experience in IT and project management, disciplinary leadership of up to 80 employees.
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
Keying Wu
Last position:
Freelance Fullstack Developer at Helaba Invest
- ChatGPT-like AI chatbot with file upload and interaction capabilities, hosted on Azure in Europe to ensure compliance with corporate data privacy regulations
- AI-powered legal document processing solution for automating the extraction of tax-related data from complex legal documents, enhancing accuracy of tax liability identification, reducing processing time, and mitigating risk of non-compliance
- Asset Manager Service portal (AMS) developed using Angular, Python, Docker, and Oracle DB, serving as a pivotal data catalog to enhance data retrieval efficiency and accuracy
- Dynamics 365 Azure integration via custom Azure Functions plugins to align CRM capabilities with unique requirements of an investment institute
Maxime Péricat
Last position:
Analytics & Marketing Consultant at Data Strategy Consulting - Péricat
As a freelancer, I help companies build and use online marketing and analytics strategically.
Together, we develop a sustainable strategy to reach your target audience, use data sensibly and in compliance with data protection, and set up your website optimally.
I rely on close, long-term collaboration – transparent, pragmatic, and without unnecessary jargon.
My goal is to make your company strong digitally and give you the tools to make informed decisions.
I work at a senior level in my role.
Skills:
Digital (Web) Analytics
Marketing Technology
Web Data Protection (GDPR & TDDDSG)
Cookies & Cookie Banners
Data Strategy
Google Analytics
Google Tag Manager
Google Ads
Digital Project Management
Patrick Upmann
Last position:
Interim Management | Consulting & Implementation | Data Deletion in SAP at BSR (Berliner Stadtreinigung)
- Topics: Business Analysis, Data Privacy, Data Management, Stakeholder Management, Conceptualization
- This project focuses on developing and implementing a strategic approach for data deletion in SAP systems. The goal is to identify the relevant data and structures during system migration to ensure both data privacy and IT system efficiency. At the same time, downtime should be minimized and regulatory requirements met.
- Development of a comprehensive approach for data deletion in SAP systems, considering data privacy and business requirements.
- Ensuring efficient and structured data transfer to the new system.
- Optimizing system efficiency and reducing downtimes during migration.
- Creating functional and technical concepts to ensure compliant and sustainable data management.
- Topic preparation: Detailed study of the "data deletion" area to lay the foundation for a structured data migration.
- Definition of project structure: Setting roles, interfaces and the project's organizational structure.
- Regulatory requirements: Analysis of data privacy regulations and business requirements to define deletion criteria.
- Approach: Developing possible scenarios and methods for data cleansing and deletion.
- Deletion concepts: Creating functional and technical deletion concepts that structure the implementation and provide clear guidelines.
- Setting deletion criteria: Defining which data and structures to delete or transfer.
- Responsibilities: Clarifying responsibilities within the project team and among stakeholders.
- Analysis of ongoing activities: Identifying and collecting existing activities in the "data deletion" area.
- Effort, cost and timeline planning: Creating estimates for resources, effort and budget.
- Implementation initiatives: Developing and executing concrete measures to apply the defined deletion strategies.
- IT system efficiency: Analyzing the existing IT infrastructure to identify optimization potential for data deletion and transfer.
- Technology trends: Evaluating new technologies and tools that can support the data cleansing process.
- Cost-benefit analysis: Assessing the financial impact of data cleansing and the introduction of new solution approaches.
- Risk management: Identifying potential risks during implementation and developing appropriate mitigation measures.
- This project lays the foundation for a sustainable and compliant data transfer to a new SAP system. With a clear approach to data deletion, it meets data privacy requirements, reduces downtimes and increases the efficiency of the new system. The results and recommendations will help companies develop a future-proof data strategy that meets legal and business needs.
Mathew Divine
Last position:
Data Science Expert and AI Strategist at Freelancer
- Built an API to ingest, clean, translate, and index EU tenders documents in Neo4j, enabling hybrid search with RAG and Cypher queries via a Streamlit dashboard
- Deployed the API on AWS Lightsail container services with CI/CD automation via GitHub Actions, ensuring stability through pytest unit and integration tests
- Designed and developed a comprehensive online course on data analysis using ChatGPT for professionals and learners, creating instructional videos and interactive Jupyter notebooks
- Utilized OBS and professional audio equipment to ensure high-quality video and audio content
- Led a CRM data normalization and cleaning project visualized via a Sankey diagram to aid customer understanding and pipeline development
- Implemented and validated a genAI-driven web crawling strategy on AWS, ensuring data quality, scalability, and CRM data augmentation
Nikolay Tonev
Last position:
Senior Cloud Data Architect at Cloudreach/Eviden (an ATOS Company)
- Architected a self-service Google Kubernetes Engine (GKE) platform for a major financial institution (Commerzbank), enabling 1000+ users across hundreds of product teams to autonomously provision resources and significantly accelerate development cycles.
- Designed a data-product-oriented platform architecture for the UK Department for Transport (DfT) to serve over 1500 direct end-users and numerous connected third-party systems, enhancing data accessibility and governance.
- Drove business growth by developing the strategic roadmap for the 'One Cloud' business line, targeting a 10% revenue increase.
- Served as a key member of the CTO Authority, providing strategic guidance on internal cloud initiatives and best practices.
Doncho Panayotov
Last position:
AI Engineer / Data Scientist at Freelance
- Designed and implemented scalable data governance frameworks for healthcare, energy, and telecom enterprises.
- Architected data models in Azure Synapse & Power BI, enabling high-performance reporting and scalability.
- Led migration of legacy BI systems to cloud infrastructure, improving efficiency and resilience.
- Acted as a technical consultant, advising clients on architecture improvements and implementation strategies.
Maziyar Khorrami
Last position:
Data Engineer at MSD Germany
- Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
- Performance Optimization of Data Ingestion of ETL Pipeline
- Development of Data Validation using Great Expectations
- Leading of the data migration for two sources exchanges
- Data Modeling in AWS Redshift
MLOps
- Model inference implementation by mlflow and AWS SageMaker
- Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
- Implementatino of Model Registry and artifactory using mlflow
- Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
- Feature importance using mlflow
Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy
Bharathi Vanganuru
Last position:
Senior Software Engineer (Individual Contributor) at European XFEL
- Electronic logbook app developed for research centers to maintain their investigations.
- Emphasizes user-driven organization of communication: experiment groups can configure information structure and notifications, while principal investigators maintain full access control.
- Real-time integration with the facility’s metadata catalogue, control system Karabo, and data analysis tool enables the automatic logging of key events, complemented by manual entries as needed.
Petru Kisalita
Last position:
Architect & Technical Team Lead & Senior Developer at Goetel GmbH
- Design, architecture & development/programming of ETL/ELT data pipelines, DWH, BI solution
- Technical project lead, POC – proof-of-concept creation
- Liaison between business units and technical teams
- Azure DevOps Boards & Jira
- Data modeling & data engineering – data warehouse & data mart
- Azure (Data Factory, Azure SQL, Azure DevOps CI/CD, Azure Data Lake V2, Business Central REST API, OData API, OAuth2 tokens)
- SharePoint lists & API for ADF, Firebird DB, Postgres DB, DB2
- Power BI (Power Query), DAX, Excel PBI add-on, GIS data
- Automated ETL process monitoring/logging, performance monitoring, error monitoring – capturing & resolution
- Index performance tuning & statistics monitoring, Transact-SQL
- Data security – MFA (multi-factor authentication) & OAuth2, MS Graph, Azure networks & firewalls, gateways, roles, user groups – with read/write permissions
- Sources – Vario Bill, Camunda, Radius, Geo Database, OTRS, PAST, MS Dynamics Business Central, Azure Blob Data Lake, SharePoint lists
Matthias Von Görbitz
Last position:
Managing Partner at IT consulting firm
Discover over 15,000 top freelancers
Statistics of experts using Data Catalog
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
3.8 years
Positions per freelancer
12
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Retail, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Human Resources
Bachelor's degree or higher
92%
Master's degree or higher
54%
Doctorate
23%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
93%
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 Germany 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 Germany using Data Catalog
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
Data catalog basics
A data catalog helps people find, understand, and trust data across a company. It collects metadata from databases, warehouses, lakes, BI tools, and pipelines so teams can search, tag, and use data with more context. Many teams also call this a metadata catalog or enterprise data catalog.
What it supports
- Data discovery and search across systems
- Business glossary and term management
- Ownership, stewardship, and data domains
- Lineage and impact analysis
- Access requests and policy context
It is common in analytics, platform, and governance work where many data sources need one clear view.
Where experts help
Companies bring in freelance specialists when a catalog must fit a cloud stack, a lakehouse, or a fast-moving governance program. In Germany, this often comes up in regulated industries, larger product teams, and international groups that need strong data coordination across locations. Remote work is common, but on-site workshops can help with naming, ownership, and glossary design.
Common tools
The ecosystem often includes Collibra, Alation, Microsoft Purview, DataHub, Apache Atlas, and cloud-native catalog features in AWS, Azure, or Google Cloud. Strong professionals know how to connect scanners, sync metadata, map business terms to technical assets, and keep the catalog useful after rollout. They also understand how catalogs interact with data quality and lineage tools.
Strong specialist profile
Good experts do more than install a product. They define the information model, tune search and classification, align with governance owners, and keep the catalog current as pipelines change.
- Clear metadata modeling
- Practical governance setup
- Good communication with data owners
- Experience with integrations and APIs
- Focus on adoption, not just setup
Why companies hire freelance help
Freelance support is useful when the internal team has the platform but not the catalog design, rollout plan, or cleanup time. It also helps when a company needs a short-term push for discovery, lineage, glossary buildout, or a migration from a legacy metadata repository. The right specialist turns a catalog into a working tool, not a forgotten portal.
Frequently asked questions
Not sure where to start with Data Catalog? These answers cover the essentials.
A strong Data Catalog gives teams one place to search for datasets, see ownership, read definitions, and trace where data came from. It is used to reduce confusion around terms, speed up analysis, and make data easier to trust. In many companies, it becomes the front door for governance and discovery.
Data Catalog and metadata repository are related, but they are not always the same thing. A repository may store metadata in a more technical way, while a catalog usually adds search, business context, glossary terms, lineage, and user-facing workflows. That is why buyers often compare it with data governance and discovery tools, not just storage systems.
Data Catalog projects often involve Collibra, Alation, Microsoft Purview, DataHub, or Apache Atlas, plus cloud services from AWS, Azure, or Google Cloud. The right choice depends on the stack, the governance model, and how much automation the company wants. A specialist should know how to connect sources and keep metadata synchronized.
A useful Data Catalog specialist usually understands data governance, metadata management, lineage, access control, and taxonomy design. SQL, cloud platforms, ETL or ELT flows, and API-based integrations are also valuable. For bigger rollouts, change management matters as much as technical setup.
A small Data Catalog cleanup may need only a focused specialist who can fix source connections, naming, and ownership rules. A broader rollout usually needs someone who can work with governance leads, platform teams, and analysts at the same time. The key is not just technical skill, but the ability to make the catalog useful for daily work.
A company should bring in Data Catalog expertise when discovery is messy, metadata is incomplete, or the existing catalog is not being used. Freelance support is also useful during a migration, a governance reset, or a cloud data platform build. In Germany, hybrid work is common, but many catalog tasks can be handled fully remote.
A good Data Catalog specialist produces a catalog people actually use. Look for clean source mapping, sensible glossary terms, reliable lineage, and clear ownership rules, not just a tool that is switched on. Strong experts also explain trade-offs and help teams keep the catalog current after launch.
Data Catalog software helps people find and understand data, while governance software often focuses more on policies, controls, and accountability. In practice, the two areas overlap, and many tools combine both. A good freelancer knows where the catalog ends and where governance workflows take over.
The average hourly rate of freelancers in Germany who have used Data Catalog in their recent projects is 106 €, which corresponds to a daily rate of about 852 € based on an 8-hour working day.
Of the freelancers in Germany who have used Data Catalog in their recent projects, 92% hold at least a Bachelor's degree, 54% hold at least a Master's degree, and 23% hold a doctorate.
On average, freelancers in Germany who have used Data Catalog in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 3.8 years.
The most common languages among freelancers in Germany who have used Data Catalog in their recent projects are German (100%), English (93%), and French (33%).
The most common industries among freelancers in Germany who have used Data Catalog in their recent projects are Information Technology (80%), Retail (67%), and Professional Services (60%).
The most common business areas among freelancers in Germany who have used Data Catalog in their recent projects are Information Technology (100%), Business Intelligence (87%), and Product Development (60%).
Main locations of FRATCH Experts, who have recently used Data Catalog
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 Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 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
