Data Architects in Germany
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Meet FRATCH Data Architects in Germany
Umut Gülac
Last position:
Data Architect at BA Technology
I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.
I delivered following projects and engagements as a freelancer.
- Data Migration of CRM System for AL-FA Objekt Service Gmbh
- Microsoft Software Resales Partnership
I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer
Technical Focus Areas
- Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
- DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
- Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
- MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
- Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.
Daryoosh Dehestani
Last position:
FP&A Data & AI Architect at Epta Group
Scope: Embedded as FP&A Data & AI Architect within the Finance function of a major European refrigeration manufacturer, leading the transformation of manual, fragmented financial reporting into an automated, governance-driven intelligence platform. Driving the shift from Excel-based controlling to structured data architecture, Power BI analytics, and AI-assisted financial operations.
Financial Data Integrity & ERP Governance
- Initiated and led GL vs. subledger reconciliation investigations, identifying and resolving structural mismatches between General Ledger and subledger data that had gone undetected prior to engagement
- Conducted asset analysis to identify items missing from General Ledger postings, surfacing gaps in fixed asset tracking and period-end completeness
- Validated SAP reports, establishing baseline data quality standards for Finance team consumption
- Established systematic SAP data validation framework ensuring ongoing integrity between ERP postings and downstream reporting outputs
Finance Reporting Transformation
- Designed and implemented a structured Transformation Project approach for converting manual Finance reports into fully automated processes
- Created and owns the Data Reporting Audit Log; a centralized tracking system capturing report owners, stakeholders, data sources, manual effort estimates, and automation opportunity scores across the Finance function
- Mapped the full reporting landscape identifying quick-win automation targets and strategic Power BI migration candidates
- Actively reducing manual Excel and PowerPoint dependency across FP&A workflows; replacing point-in-time snapshots with live, governed data models
Power BI & Analytics Enablement
- Introduced and presented Power BI as the strategic reporting platform to Finance leadership, building internal buy-in for the BI transformation roadmap
- Designed initial Power BI architecture aligned with SAP, Salesforce and Oracle data structures and FP&A reporting requirements
- Established report ownership, governance documentation, and data lineage standards enabling sustainable self-service analytics across the Finance team
Transformation Infrastructure & Collaboration
- Configured and deployed Jira as the transformation project management hub, establishing structured sprint workflows, backlog management, and progress visibility for Finance IT initiatives
- Proposed and initiated a dedicated FP&A Communication & Transformation Hub, a structured cross-functional forum aligning Finance, IT, and business stakeholders around the reporting transformation roadmap
- Positioned the Finance function as an active driver of data governance and digital transformation within the broader organization
Outcomes
- GL/subledger reconciliation gaps identified and investigation framework established within first two weeks of engagement
- Data Reporting Audit Log deployed; first structured inventory of Finance reporting landscape in company history
- Power BI transformation roadmap presented and approved by Finance leadership
- Jira-based project governance live; Finance transformation now tracked with full sprint visibility
Technologies: SAP FI/CO · Power BI · DAX · SQL · Excel (advanced) · Power Query (M) · Power Automate · VBA · Jira · Microsoft 365 · SharePoint · Salesforce (Sales Data) · Oracle HCM · Python
Alexander Zhirov
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Oleg Orlov
Last position:
Senior Software Developer / BI Integration Developer Power BI, C# at Telecommunications
Embedded Analytics & AI-assisted BI
Design and development of an integrated analytics solution based on ASP.NET Core, Power BI Embedded, and LLM services to provide contextual business information.
Development of an AI agent with Function/Tool Calling for secure orchestration of REST APIs, SQL data sources, and technical services within defined business processes.
Build-up of automated BI workflows including workspace management, deployment processes, and scheduled refresh via the Power BI REST API.
Implementation of secure service-to-service communication with Microsoft Entra ID and service principal, as well as integration into existing enterprise system landscapes.
Technologies: ASP.NET Core, C#/.NET, Power BI Embedded, Power BI REST API, LLM API, AI Agents, Function/Tool Calling, Entra ID
Laurin Hagemann
Last position:
Software Architect (Freelance) at Care4Sure
- Delivered MVP-focused full-stack architecture for a health-sector client: Vite/React frontend, backend services on Google Cloud Run, and Supabase for database plus IAM/authentication.
- Supported product requirements engineering and prioritized cost-aware workload placement, implementing browser-side/edge computation where feasible before moving logic to backend services.
Uwe Schwarz
Last position:
Technical Program Lead IPv6 Migration at Deutsche Rentenversicherung (RP, BW)
- Technical program ownership for the IPv6 migration at DRV RP and DRV BW, with a focus on migration planning, execution structure, and cross-functional technical coordination.
- Designed and implemented an operational control model with dashboard, action board, KPI portfolio, risk register, and decision index to translate technical topics into structured delivery artifacts.
- Coordinated technical groundwork for architecture and rollout across IPv6 addressing, segmentation, dual-stack target design, test-lab planning, and cross-team dependencies.
- Supported security and compliance-related requirements in the context of BSI, NIS2, and critical infrastructure, translating them into traceable evidence, risks, and management reporting.
- Achievement: Established a reusable intake-to-governance workflow for systematically capturing technical actions, risks, open issues, and evidence requirements.
- Achievement: Created an operational baseline for technical program execution with measurable KPIs, clear ownership, and transparent decision support.
Marco Lindner
Last position:
Senior IT Consultant | Cloud Data Engineer | Infrastructure Architect at Hannover Rück SE
Built an enterprise data lakehouse platform on Azure Databricks
Developed production data pipelines and governance structures
Implemented private cloud infrastructures using Terraform
Introduced modern CI/CD standards in Azure DevOps
Implemented secure IAM and governance concepts
Developed scalable PySpark and Delta Lake frameworks
Supported self-service analytics and data product approaches
Provided architecture and platform consulting for enterprise data initiatives
Built a central DataHub architecture for insurance data
Integrated multiple subsystems into a lakehouse platform
Introduced data governance and data lineage
Supported modern analytics and reporting standards
Optimized data delivery for business and analytics teams
Ludo Prokop
Last position:
Senior Consultant at Insurance
- DWH modernization
- Migration from Informatica PowerCenter to IDMC/CDI
- Migration from IBM DB2 to Databricks
Technologies: Informatica IDMC, Databricks
Waldemar Biller
Last position:
Software Architect for Product Data Management Tool at Ferchau Contract GmbH
- Defining the software architecture
- Designing and developing modules
- Assisting internal staff with learning and onboarding
- Tools: SAP CAP / CDS, Java 21, SAP HANA, SAP Business Technology Platform (BTP)
Ralph Behrens
Last position:
Senior Solution Architect Cloud, Data & AI at Sogeti Deutschland GmbH – Part of Capgemini
Evaluation, structuring, and handling of complex tenders for Sogeti as well as as part of larger Capgemini proposals. Focus on analyzing demanding customer requirements, deriving solid solution concepts, and translating technical, functional, and commercial aspects into convincing proposal storylines. In close alignment with delivery, sales, account, and bid teams, scalable and implementable Quality Engineering solutions were designed, evaluated, and prepared for customer decisions. This included selecting suitable role profiles and right-shore staffing options, assessing available skills and capacities, as well as the commercial preparation of reliable price and effort calculations.
A special focus was on bid management and handling service proposals (RfP/RfI analysis), solution design, presentation and management materials, as well as the functional and technical evaluation of customer requirements in the context of Quality Engineering & Testing, agentic AI-supported test automation using modern quality assurance approaches.
SOGETI projects:
- BMW: Development of a test strategy including test management, test automation, and provision of a rightshore delivery model.
- GEA: SAP Business Assurance and Quality Engineering for an SAP rollout including test governance, test automation, AI agent layer, and hypercare concept.
- AIXTRON: SAP S/4HANA Cloud migration explore phase with QA assessment, testable blueprint structure, staffing, and scalable Sogeti delivery approach.
- Deutsche Glasfaser: Quality Engineering & Testing for DG development squads, including ServiceNow and Salesforce, testing automation and governance.
- ERGO: RfP/proposal support for Managed Service Test Data Provisioning as well as a Jira/Atlassian rollout with assessment, target picture, MVP, rollout, and governance.
- Munich Re: Proposal and solution design in the insurance environment with a focus on test data provisioning, process analysis, compliance, and automation.
- BWI: Project/proposal context in the public/IT service environment with reference to Quality Engineering, Test Factory, and digital transformation support.
- Rolls-Royce: Proposal/project support in the Sogeti context with a focus on structured RfP analysis, solution design, and customer-oriented proposal preparation.
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.
Vili Dhamo
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
- Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
- Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
- Orchestrated pipelines with Azure Data Factory
- Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
- Led the Data Engineering team (3 members) in a functional role
- Conducted workshops to optimize and stabilize the data platform and the development process
- Collected and prioritized new requests, maintained the product backlog
- Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS SharePoint, Mural
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
Nima Nooshi
Last position:
Co founding LLM Engineer at LLM Ventures
- Co-founded an AI venture focused on building production-grade LLM applications and agentic systems
- Designed and implemented multi-agent AI workflows for financial and trading applications
- Developed LLM-powered copilot architectures for portfolio analysis, trade management, and personalized user coaching
- Built on-device and edge-deployed inference applications, optimizing models for low latency, privacy, and resource-constrained environments
- Led system architecture decisions across model selection, orchestration, state management, and deployment
Kai Sieveke
Last position:
Demand Manager, Analyst, Process Consultant
- Integrating system architecture, business analysis, requirements engineering, and process consulting
- Managing business unit needs toward IT and implementation
- Capturing requirements in JIRA and breaking them down into epics
- Overseeing internal projects and programs, including stakeholder management and reporting
- Handling requirements from traditional IT developments to IoT integrations and SAP subsystem replacements
- Implementing current legal regulations (MAKO, EnWG, EEG, GWG, StromGVV, GasGVV, StromNEV, GasNEV)
- Applying agile methods (Agile, SAFe, ITIL, Scrum, Kanban, DDD, IaC, CI/CD, DevOps, automation, ETL, OOA, OOD, MDA, BPMN, BPM, UML, marketing automation, data science, ML, AI, GenAI, LLMs)
- Using tools like JIRA, SharePoint, MS Office, MS Project, MS Dyn CRM, VMware ESX/ESXi, BSI IT-Grundschutz, BSI C5, NIST, MS Azure, Typo3, mail automation, Docker, Kubernetes, OpenStack, OpenShift, Terraform, Ansible, SQL, REST, SOAP, Git, GitLab, LoRaWAN, SAP IS-U, S/4HANA, USU, KUGU, AbSys, sensors, MQTT
Discover over 15,000 top freelancers
Data Architects statistics
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
3.5 years
Positions per freelancer
15
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
90%
Master's degree or higher
50%
Doctorate
7%
Certifications per freelancer
5
Most common languages
German, English, Russian
Speak two or more languages
98%
Based on our profile pool as of 26 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this role 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 for Data Architects in Germany
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 26 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the role
Data model design
A Data Architect turns business needs into a data design that teams can build and trust. The work covers source analysis, domain models, master data, integration patterns, and the rules that keep reporting consistent across systems.
- Define target data architecture and data flows
- Design warehouse, lakehouse, or data lake structures
- Set naming, lineage, and data quality standards
- Align business terms with technical models
Delivery focus
Strong Data Architects do more than draw diagrams. They make sure platforms are usable for analytics, BI, machine learning, and operational reporting. Common deliverables include architecture blueprints, data models, governance guidelines, and migration plans for legacy systems.
They are often brought in when a company needs to untangle fragmented ERP, CRM, or product data, or when new cloud platforms must fit existing landscapes in Germany and across global teams.
Key skills
A good Data Architect understands both business processes and technical detail. Look for experience with data integration, SQL, data warehousing, metadata management, security concepts, and cloud data platforms.
- Data modeling and schema design
- ETL and ELT design
- Governance, privacy, and access control concepts
- Cloud and hybrid architecture thinking
- Clear communication with engineering and business stakeholders
Tools and stacks
The right stack depends on the environment. Many Data Architects work with SQL, Python, Spark, dbt, Snowflake, BigQuery, Azure Synapse, Databricks, and common BI tools such as Power BI or Tableau. In enterprise settings, SAP data landscapes and MDM tools often matter as well.
What matters most is not tool recall alone, but the ability to fit tools into a stable architecture that can scale and stay maintainable.
When to hire
Companies bring in a freelance Data Architect when a platform change needs structure fast, when a migration is already underway, or when internal teams disagree on the target design. Interim support also helps during cloud modernization, data governance setup, or before a major analytics rollout.
For German companies, short-term external support is especially useful when a project needs precise documentation and close coordination with internal IT, BI, and security teams.
What strong experts do
The best Data Architects reduce complexity without creating new silos. They question weak assumptions, define clear standards, and explain trade-offs in plain language. They work well with engineers, analysts, product owners, and enterprise architects.
- Translate business goals into a practical target architecture
- Spot risks in integration, security, and data quality early
- Keep documentation current and usable
- Balance speed, governance, and long-term maintainability
Frequently asked questions
Quick answers to the questions that come up most around Data Architects.
A Data Architect designs how data should move, be stored, modeled, and governed across systems. On a freelance project, that usually means assessing the current landscape, defining the target architecture, and giving engineering teams a clear implementation path. The role is about structure and decisions, not only documentation.
Look for strong data modeling, integration design, and governance skills. A good Data Architect also needs hands-on knowledge of SQL, cloud data platforms, metadata, and security concepts. Just as important is the ability to explain trade-offs to both technical and business stakeholders.
A data engineer focuses on building pipelines and making data flow reliably. A BI architect is usually more centered on reporting layers and semantic models. A Data Architect sits above both and defines the overall structure, standards, and target design that those roles then implement.
A freelancer is often the better choice when you need design work for a specific initiative, such as a migration, cloud setup, or governance rollout. It also makes sense when the need is urgent and you want senior guidance without a long hiring process. Many companies use a freelance Data Architect to unblock a project before deciding on a permanent role.
Typical outputs include target architecture diagrams, data domain models, integration patterns, migration roadmaps, and governance principles. A strong Data Architect also documents assumptions and dependencies so teams can build with fewer surprises. The best deliverables are practical enough for engineers to use right away.
Yes, most of the work can be done remotely if the communication setup is clear. For some projects in Germany, especially in larger enterprises, on-site workshops are helpful at the start to align stakeholders and access complex system landscapes. Hybrid collaboration is often the most practical option.
Review how they describe past architecture decisions, not just the tools they know. A strong Data Architect can show how they handled data quality, security, integration, and long-term maintainability in real projects. Good signs are clear thinking, structured documentation, and strong stakeholder alignment.
Searchers sometimes use adjacent titles such as Data Solution Architect or Enterprise Data Architect when they mean this kind of work. In some companies, the role is also described as a data platform architect, especially when cloud architecture is central. The exact title matters less than whether the person can shape a reliable data foundation.
The average hourly rate for Data Architects in Germany is 100 €, which corresponds to a daily rate of about 801 € based on an 8-hour working day.
Of the freelancers working as Data Architects in Germany, 90% hold at least a Bachelor's degree, 50% hold at least a Master's degree, and 7% hold a doctorate.
On average, freelancers working as Data Architects in Germany have 20 years of professional experience, with a single engagement typically lasting around 3.5 years.
The most common languages among freelancers working as Data Architects in Germany are German (100%), English (95%), and Russian (13%).
The most common industries among freelancers working as Data Architects in Germany are Information Technology (90%), Banking and Finance (60%), and Professional Services (58%).
The most common business areas among freelancers working as Data Architects in Germany are Information Technology (100%), Business Intelligence (88%), and Product Development (73%).
FRATCH Data Architects main locations
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 
Berlin Request a free demo
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Philipp Thomaschewski
FRATCH CEO
