Product Data Management Experts in Germany
matched in minutes with vetted, available freelancersHire experts who structure product records, govern bills of materials and connect CAD, ERP and PLM workflows. Get precise support for data migrations, classification and lifecycle processes through fast matching with vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used Product Data Management
Alwin G.
Last position:
IT Interim Manager & AI Strategist
- Founder of CheironX: AI-supported GRC management (ISO 27001, BSI IT-Grundschutz, TISAX, DORA)
- Strategic focus on Agentic AI and GenAI for modern IT Governance, Risk & Compliance Management
- IT interim management and strategic consulting
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
Philip S.
Last position:
Interim Management - OPEX, BPM, LEAN CI, Quality at SCOTTSPOT
Andreas W.
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 S.
Last position:
Project Manager at Nordex
- Strategy to migrate data after the takeover of a company
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 S.
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 P.
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 K.
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
Thomas P.
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
Cedric T.
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 G.
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 P.
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.
Martin M.
Last position:
Requirements Engineer at MCM Modern Engineering UG HB
- Analysis of the current process
- Development of the target processes
- Support for the implementation of improvements in an SAP-enabled program
- Simplification of customer contact initiation
- Streamlining internal processes through automated real-time verification of claim relevance
- Creation of use cases
Axel K.
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
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
2.8 years
Positions per freelancer
14
Top business areas
Product Development, Project Management, Quality Assurance
Top industries
Manufacturing, Automotive, Professional Services
Certification focus areas
Product Development, Project Management, Information Technology
Bachelor's degree or higher
84%
Master's degree or higher
37%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
95%
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 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Product Data Management experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Manufacturing (86%)
- Automotive (66%)
- Professional Services (46%)
- Information Technology (41%)
- Healthcare (29%)
- Construction (25%)
- Food and Beverage (25%)
- Energy (24%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What PDM covers
Product Data Management, often called PDM, controls the digital information created around a product. It organizes CAD files, technical documents, bills of materials, specifications, revisions and approval records. A reliable PDM setup gives teams one governed source for product information and makes each change traceable.
Where it is used
PDM supports products with complex designs, many variants and strict release processes. It is common in industrial manufacturing, automotive, aerospace, electronics, medical technology and machinery. Companies use it to coordinate design work, protect technical knowledge and move accurate product data into production.
- Manage CAD files, documents and metadata
- Control revisions, versions and approvals
- Structure bills of materials and product variants
- Prepare data for ERP, PLM and manufacturing systems
Ecosystem and tooling
PDM work often connects CAD systems with PLM and ERP environments. Common ecosystems include Siemens Teamcenter, PTC Windchill, Dassault Systèmes ENOVIA and integrations with tools such as SolidWorks, CATIA, NX and Creo. Strong specialists also understand APIs, data models, access controls, workflow configuration and migration tooling.
When companies need support
Companies bring in freelance expertise during system selection, implementation, consolidation or recovery from inconsistent product records. Specialists can map legacy structures, define naming and classification rules, clean duplicate data and prepare controlled migrations. In Germany, this is especially relevant for distributed manufacturing teams working across plants, suppliers and remote or on-site locations.
- Replace disconnected file shares with governed records
- Standardize part numbers, attributes and document states
- Connect engineering data with procurement and production
- Improve search, reuse and change visibility
What strong experts deliver
Effective PDM professionals combine product data knowledge with process discipline. They can translate engineering requirements into practical workflows without making daily work harder. Their deliverables may include a data model, migration plan, role and permission concept, configured lifecycle states, integration specifications and clear operating guidance.
How to assess fit
Look for specialists who can explain how they handled revisions, effectivity, variants, permissions and engineering change processes in a comparable environment. Ask how they validate migrated records and measure data quality without weakening governance. For German teams, clarify collaboration language, plant access needs and how the professional will work with engineering, manufacturing, procurement and IT stakeholders.
Frequently asked questions
Curious about Product Data Management? Here are the answers that come up again and again.
Product Data Management is used to organize and control technical product information throughout design and release. It manages CAD files, documents, bills of materials, revisions, approvals and related metadata so teams work from trusted records.
PDM focuses mainly on product files, structures, revisions, access and engineering change control. PLM covers a broader product lifecycle, including requirements, compliance, manufacturing, service and portfolio processes, while PDM is often one part of that environment.
A strong Product Data Management specialist usually understands CAD administration, PLM processes, ERP integration and bill-of-materials structures. Useful adjacent skills include data migration, SQL, APIs, workflow design, classification, permissions and engineering change management.
The right PDM freelancer should have worked with a product structure and release process comparable to yours. The relevant depth depends on data volume, system complexity, integrations, regulatory demands and the condition of legacy records, not simply on time spent with a tool.
Product Data Management work can often be delivered remotely through secure access, workshops and documented configuration reviews. On-site visits may still help with plant processes, restricted systems, hardware-linked workflows or stakeholder sessions, so agree access and language expectations early.
Assess whether PDM deliverables make product data easier to find, change, approve and reuse without reducing control. Review the proposed data model, migration validation, permissions, audit trail, workflow usability and documentation, then ask for examples of issues the specialist identified and resolved.
Product Data Management commonly connects CAD applications with PLM, ERP, manufacturing and document systems. Examples include Teamcenter, Windchill, ENOVIA, SolidWorks, CATIA, NX, Creo and enterprise resource planning environments, with the exact integration depending on the company’s architecture.
Before taking on PDM work, clarify the target system, source data, product structures, ownership rules, integrations and release workflow. Also confirm security requirements, stakeholder availability, remote or on-site expectations and how success will be checked after configuration or migration.
The average hourly rate of freelancers in Germany who have used Product Data Management in their recent projects is 96 €, which corresponds to a daily rate of about 770 € based on an 8-hour working day.
Of the freelancers in Germany who have used Product Data Management in their recent projects, 84% hold at least a Bachelor's degree and 37% 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 2.8 years.
The most common languages among freelancers in Germany who have used Product Data Management in their recent projects are German (100%), English (95%), and French (24%).
The most common industries among freelancers in Germany who have used Product Data Management in their recent projects are Manufacturing (86%), Automotive (66%), and Professional Services (46%).
The most common business areas among freelancers in Germany who have used Product Data Management in their recent projects are Product Development (96%), Project Management (82%), 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 
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Philipp Thomaschewski
FRATCH CEO
