Product Data Management Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Product Data Management
Henning Uiterwyk
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
Philip Scott
Last position:
Interim Management - OPEX, BPM, LEAN CI, Quality at SCOTTSPOT
Thomas Peter
Last position:
Lifting Device Designer at TP-Produktdesign
- Design of a 3-point quick coupling for tractor lifting attachment
- Development of a bracket for a tow flange device
Andreas Winters
Last position:
Enterprise Architect at Own development / IP of CAMCO Engineering UG
UEF 3.0 · Semantic Government Overlay (SGO) · Autonomous Systems (UAS / dual use)
- Designed: Semantic Government Overlay (SGO) – AI-guided administration without replacing existing specialist procedures. Read-only semantic layer over registers and specialist processes based on the Federal Information Management (FIM). Decision authority remains with the case worker (architecture principle).
- Developed: Reference architecture with source-backed, derived statements (Executable Ontologies OWL/RDF/SHACL). Technically guaranteed purpose limitation and no-write-path principle in specialist data – auditable, without a central data pool.
- Anchored: Regulation as a design principle: EU AI Act (high-risk obligations for public-sector AI, fundamental rights impact assessment under Art. 27), GDPR, NIS2, and administrative automation limits (§ 35a VwVfG, § 31a SGB X) as technical control points in the architecture.
- Created: Methodical tool for pilot organizations: data pipeline assessment (phase 0), compliance blueprint, and management summary as a decision-ready package for public administration.
- Specified: UEF 3.0 as a successor architecture to TOGAF – decision paper, canonical ontology, six-layer architecture, read/actuate boundary, federation registry, terminology concordance, and release delta as a closed specification status.
- Architected: AI-native mission OS for autonomous UAS and ground robotics as a tactical layer on top of a separately approved autopilot. Run-time assurance according to ASTM F3269-21 (Simplex pattern): the verified safety controller keeps authority, the AI function provides suggestions.
- Designed: Three-tier architecture – Tier 0 autopilot with 650 Hz flight control on RTOS, Tier 1 AI OS with semantic world model and multi-agent cluster, Tier 2 swarm and ground mesh. Zenoh as the primary fabric, MAVLink as the only authenticated command path (single writer). Result: graceful degradation – loss of the mission, not of the aircraft.
- Secured: Two-gate chain on the read/actuate boundary – governance gate (can-question: AI Act risk class per actuation, enforced human oversight under Art. 14, immutable log) before the RTA safety monitor (is-it-correct question: flight envelope, geofence, energy reserve) with revert to the baseline controller.
- Anchored: Dual-use architecture with common core and build-time fork instead of runtime switch. Three separate legal levels: civil variant – UAS under the EASA Basic Regulation (EU) 2018/1139 with the limited applicability under Art. 2(2) of the AI Act, ground robotics under the Machinery Regulation 2023/1230 with the full high-risk obligation chain, Cyber Resilience Act for both; unarmed carrier variant as defense material under AWG/AWV and Dual-Use Regulation 2021/821 (BAFA approval); armed variant under KrWaffKontrG. Each variant lives under exactly one dominant legal regime. Evidence base: AI BOM, SBOM, and complete data lineage.
- Analyzed: System analysis and realignment of grown engineering system landscapes. Approach concept for consolidation without migration – semantic layer over the existing sources instead of data transfer. Result: decision-ready implementation concept including an evaluation model for the target architecture.
Andreas Schneider
Last position:
Project Manager at Nordex
- Strategy to migrate data after the takeover of a company
Abdelkader El Moumane
Last position:
Lead Business Analyst (PIM)
- Further development and optimization of the PIM system (e.g. data modeling, interfaces, user experience)
- Analysis, structuring, and professional evaluation of business requirements in close coordination with business units and stakeholders
- Translating business requirements into functional and technical concepts (business & solution design)
- Designing and further developing the target PIM architecture including data models, object structures, versioning, and lifecycle concepts
- Defining interfaces, integration concepts, and data flows between PIM, eCommerce, ERP, and other systems
- Quality assurance in close collaboration with business units and the development team
- Effort estimations for analysis, design, and testing activities
- Agile, Scrum, 4APortal, SAP ERP, SAP eCommerce (Hybris)
Sven L.
Last position:
Group CTO at apo.com Group
- Situation: Inherited a patchwork of aging proprietary systems accumulated over 20+ years — custom-built shop, pharmacy operations, logistics, and product data management. No standardization, no automation, no modern delivery practices.
- Team: Found a centralistic hero culture with one manager handling more than 20 direct reports. Removed the bottleneck, replaced low performers, brought resistant team members back on track or managed them out. Hired fresh talent that brought new energy and capability.
- Delivery: Unified nine brands into a single platform, improving delivery speed by roughly 10x and eliminating cross-brand inconsistencies. Launched a new mobile app that tripled mobile revenue share within 12 months.
- AI: Implemented AI coding tools across development departments. Continuously working on trainings and knowledge sharing for developers. Delivered analytics and agentic automation for customer care inbound emails, and initiated agentic call automation.
- Operations: Introduced automated build and deployment pipelines, initiated cloud migration, and brought the core pharmacy system onto a maintainable, current foundation.
- Governance: Took back project prioritization from ad-hoc business demands by introducing transparent capacity planning — the biggest “no” enforced and the most impactful change for the organization.
Alexander Schulze
Last position:
AI Consultant for AI Voice Bot System at Rudolf Hörmann GmbH & Co.KG
- Consultant for system architecture, AI agents & integration, coach for data & process logic, Graph-RAG approaches, security and data protection.
- On-premise AI solutions with high compliance and performance requirements.
- Architecture decisions, operational setup, strategic prioritization & deployment.
- Technologies: LiveKit JS SDK, LiveKit Agents, Web Audio API, JS, AudioWorklet, Loki, vLLM, Zscaler, Docker, Neo4j, MySQL, Python.
- Models: GPT-OSS 20B, Whisper large v3 turbo, Qwen3-TTS.
Gregor Pestsov
Last position:
Engineering Data Management Project Manager
Technical and commercial risk assessment for an investment project in the hardware sector (scaling potential, liability risks, operational processes) Process consulting for two SMEs in the engineering environment, focusing on workflow digitization, PLM
Rafal Kaniecki
Last position:
Development Engineer at Hexagon Purus
- CAD system: SolidWorks 2021
- PDM database: HXP SolidWorks
- Product: mobile hydrogen refueling station
- Handling and implementing change requests
- Independently developing products for new applications
- Reviewing and approving production and assembly drawings
- Providing technical support to engineering service providers
- Collaborating closely with purchasing and quality teams
- Developing and achieving cost reduction goals
- Planning and executing concept validations
- Independently creating solution proposals and technical concepts for new ideas
- Establishing and maintaining supplier relationships
Cedric Tiogo
Last position:
B2B Freelance Design Engineer for Special-Purpose Machinery at FEM-Composites GmbH
- Cost estimation for a hydraulic system, taking into account the costs over the entire product life cycle and optimizing the technical specifications.
Mauricio Godinez
Last position:
Design Engineer at Butting CryoTech GmbH
- Creation of complete 3D designs and design drawings
- Evaluation of requirement specifications and customer specifications
- Execution of partial steps in technical work preparation according to specifications and documents, including project support
- Contact person for internal and external customers in design projects
- Design and calculation of piping and components for cryogenic media and low-temperature applications
- Support with finite element calculations
Ulm Paunel
Last position:
DataStage ETL Expert at ING Bank
- Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
- Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
- Storage of the silver layer on Hadoop and the gold layer in Oracle.
- Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
- Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
- Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
- Versioning changes in GitHub and deployment via the CI/CD portal.
- Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
- Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
- Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
- Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
- Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.
Axel Kurz
Last position:
Project Manager
- ERP selection project at an automotive supplier in Regensburg to choose a successor system for a custom-built legacy solution
- Conducting interviews with specialist departments
- Creating a criteria catalog
- Organizing and running workshops
Hüseyin Özgün Gönüllü
Last position:
Freelance Mechanical Engineer - Designer at Gridesign
Conception and detailed design of mechanical systems.
CAD modeling, drawings and calculations.
FEM, motion analysis and reverse engineering.
Preparation of technical proposals and claim management.
AIRBUS A-320 Assembly Station.
AIRBUS A-350 Manual Assembly Station.
FORD Truck R&D Prototype Manufacturing Station.
Discover over 15,000 top freelancers
Statistics of experts using Product Data Management
Aggregated from the professional profiles of matched freelancers.
Experience
26 years
Position duration
3 years
Positions per freelancer
14
Top business areas
Product Development, Project Management, Quality Assurance
Top industries
Manufacturing, Automotive, Information Technology
Certification focus areas
Product Development, Project Management, Information Technology
Bachelor's degree or higher
82%
Master's degree or higher
35%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
96%
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 Product Data Management
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 is
Product Data Management, often called PDM, keeps product files, metadata, revisions, and approvals under control. It is used to store the right design information in one place and make sure teams work from the latest version. In many companies, it sits close to PLM and CAD systems.
Typical work
- Set up file structures, naming rules, and revision logic
- Manage item master data and change workflows
- Connect CAD tools with PDM or PLM systems
- Clean up product records and release processes
- Support data migration and system rollouts
Common stack
Strong specialists know the ecosystem around the PDM core. That often includes Siemens Teamcenter, PTC Windchill, SOLIDWORKS PDM, Autodesk Vault, and related CAD, ERP, and PLM tools. They also understand permissions, BOM handling, and workflow configuration.
When to bring in help
Companies bring in freelance expertise when product data is inconsistent, releases are slow, or a system rollout needs outside hands. This is common in manufacturing, automotive, machinery, and industrial equipment teams in Germany where product data must stay clean across sites and suppliers. External specialists also help when internal teams lack capacity for migration or process design.
What good specialists do
- Map real product processes before changing the system
- Balance structure, usability, and governance
- Work well with engineering, operations, and IT
- Document rules so teams can keep using them
- Spot data risks before they affect release quality
Why companies choose it
Good Product Data Management reduces duplicate files, broken revisions, and approval mistakes. It supports traceable changes and smoother handoffs between design and production. For freelancers, it is a space where process thinking matters as much as tool knowledge.
Frequently asked questions
Curious about Product Data Management? Here are the answers that come up again and again.
Product Data Management covers the way product files, item data, revisions, and approvals are stored and controlled. It helps teams keep one trusted view of product information across design, production, and release work. In practice, it is the layer that keeps CAD output and related records organized.
PDM focuses on product files, versions, metadata, and release control. PLM is broader and also covers lifecycle processes, collaboration, and often downstream business steps. Many companies use PDM as the core data layer inside a wider PLM setup.
A strong Product Data Management setup often works with systems like Siemens Teamcenter, PTC Windchill, SOLIDWORKS PDM, and Autodesk Vault. It also connects to CAD and ERP tools so data moves cleanly between design and operations. The exact stack depends on the product and the company structure.
Besides Product Data Management, look for skills in CAD data handling, workflow design, master data quality, and system integration. Understanding BOMs, permissions, and release processes is also important. The best specialists can talk to both engineering teams and IT without losing the process view.
A smaller Product Data Management task may only need one specialist with solid tool knowledge and process sense. A migration, rollout, or governance redesign usually needs deeper experience because many teams and data objects are involved. The right level depends on how much structure must change and how many systems are connected.
Yes, much of Product Data Management can be done remotely, especially analysis, configuration, documentation, and testing. On-site time can help when teams need workshops, process mapping, or closer work with shop floor and engineering groups. In Germany, many companies use a mix of both.
A good PDM specialist explains how product data flows, where rules belong, and how to prevent errors before they spread. Look for clear examples of migrations, workflow setup, change control, and stakeholder coordination. Strong work leaves the system cleaner, easier to use, and easier to govern.
Freelancers working on Product Data Management should expect a mix of process work, tool configuration, and support for business users. Projects often involve older data structures, strict release rules, and many stakeholders. Clear communication and careful documentation matter as much as technical setup.
The average hourly rate of freelancers in Germany who have used Product Data Management in their recent projects is 99 €, which corresponds to a daily rate of about 791 € based on an 8-hour working day.
Of the freelancers in Germany who have used Product Data Management in their recent projects, 82% hold at least a Bachelor's degree and 35% hold at least a Master's degree.
On average, freelancers in Germany who have used Product Data Management in their recent projects have 26 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Germany who have used Product Data Management in their recent projects are German (100%), English (96%), and French (23%).
The most common industries among freelancers in Germany who have used Product Data Management in their recent projects are Manufacturing (86%), Automotive (67%), and Information Technology (43%).
The most common business areas among freelancers in Germany who have used Product Data Management in their recent projects are Product Development (94%), Project Management (83%), and Quality Assurance (67%).
Main locations of FRATCH Experts, who have recently used Product Data Management
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.
Munich 
Stuttgart Request a free demo
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Philipp Thomaschewski
FRATCH CEO
