Data Architects in Germany
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Meet FRATCH Data Architects in Germany
Ali B.
Last position:
Domain Architect Data & IT/OT at Tata-steel
Projects: Assessment, Migration, Modernisation, Strategy, Principles
- Leading the assessment of the current database landscape across different Tata-steel IT/OT factories
- Aligning with the strategy and developing data principles for use across the enterprise by all factories to improve quality
- Simplifying the data landscape by reducing the number of tools used for extraction, transformation and analysis
- Leading the review of current data governance tools and the selection of data governance tools
- Proposing the right solution for the Drones use case to store and integrate data on-premises for OT, as well as AI in the cloud
- Brainstorming with OT departments on how to position historians as fit for purpose within OT and IT
- Examining Oracle UELA with Procurement and guiding executive stakeholders in decision-making
- Leading the sizing and cost assessment with Procurement for Oracle ExaCC for the coming years
- Creating a roadmap for Domain Data & IT for the next two to five years to present company-wide
- Setting up the migration strategy and identifying Oracle candidate databases to migrate to Oracle Exacc
- Guiding Solution Architects towards a solution using the principles created for the TATA DNA Platform
- Providing the strategy for on-premises and cloud backup and archiving using IBM Prospect, Azure and OCI
- Creating a standard reference architecture for data environments and tools for ETL and reporting for advanced analytics
Key Technologies: Oracle, Sequel Server, IBM DB2, Github, SAP, Databricks, Azure, Beaver, Oracle ExaCC, Spotfire, Azure Purview, ETL Tools, PowerBI, Tibco DataVirtualization, TIBCO spotfire, DataBricks, Azure Edge Apache Airflow, Sql server, Azure Data factory, Azure Blob Storage, logic apps, power-apps, Azure File Synch
André G.
Last position:
Financial Reporting Consultant at Client anonymized (services sector)
Financial reporting as an MVP. Follow-up assignment.
- Reports on profit and loss, balance sheet and cash flow
- Budget and personnel metrics (FTE)
- Implementation as an MVP with a fixed scope
Henry M.
Last position:
Restructuring of the Datacenter of ACS Solutions at ACS Solutions GmbH
Details & Responsibilities:
Responsible for ACS Datacenter operations at all locations for over 10 years. This includes more than 3.500 virtual systems for over 100 Datacenter customers with + 20.000 users worldwide. The associated annual revenue volume is 7 Mio. Euro.
Introduction of an HCI platform to replace the previous “Legacy” platform. Project volume 2 Mio. Euro
About the company:
ACS Solutions GmbH stands for innovative and pioneering structures in information technology. Holistic consulting and individual, future-proof solutions for medium-sized companies. Datacenter and Managed Service Provider with three Datacenter locations in Germany and more than 40 employees.
Uditha W.
Last position:
Data Science Tutor at University of Europe for Applied Sciences
- Taught Python, Pandas, data analysis, visualization and Power BI to 250+ students.
- Guided practical projects from data preparation and exploratory analysis through visualization and dashboard creation.
- Explained complex analytical concepts clearly to audiences with different levels of technical experience.
Emanuel F.
Last position:
Interim Architect & Data Taskforce at Freelancer / Project Assignments
- Data Engineering: Design and implementation of scalable data pipelines
- Legacy migrations to Microsoft Fabric (Lakehouse, Dataflows Gen2, Pipelines)
- BO Universe migrations to MS Fabric / Semantic Models / Power BI
- Taskforce for data-driven transformation projects involving Azure Fabric / Oracle / MSSQL
Andreas W.
Last position:
Self-employed Software Developer at amw-software.net
Gökan K.
Last position:
DATA ANALYST & DATA ARCHITECT at Labor Becker Medizinisches Versorgungszentrum
- Creation and optimization of data-based reports and dashboards in Microsoft Power BI
- Controlling of sales activities
- Contribution to the general Data Governance project topic
- Use of SQL data queries for decision-making on data-related issues
- Administration of Power BI users and permissions
Deepa K.
Last position:
Data Analyst – BI Lead Engineer at Novartis
- Leading enterprise BI transformation across Power BI & Microsoft Fabric, delivering scalable data models, automated reporting, and high-performance analytics solutions for commercial and operational leadership.
- Building and optimizing Power BI Dataflows, Fabric Lakehouse datasets, semantic models, and automated reporting pipelines to improve data scalability, governance, and reporting performance.
- Driving dashboard modernization and KPI governance by translating complex business requirements into executive-level insights, interactive visualizations, and decision-ready analytics.
- Designing end-to-end Microsoft Fabric architectures integrating data ingestion, transformation, virtualization, and enterprise reporting across cross-functional business domains with SAP BW to Qlik to Power BI migration.
- Delivering AI-enabled reporting capabilities, threshold-based alerting, and automation frameworks within the Power BI ecosystem to accelerate business decision-making.
- Partnering with commercial leadership, analytics teams, and IT stakeholders to standardize KPIs, optimize BI strategy, and deliver scalable, business-critical reporting solutions.
- Recognized for combining strong stakeholder leadership, technical architecture expertise, and business-driven analytics to deliver impactful enterprise BI transformation initiatives.
Bruno M.
Last position:
Enterprise Architect at Hornbach
- Lead enterprise architecture, data and AI strategy initiatives across business domains, value streams, SAP, cloud, integration, process intelligence and governance, aligning transformation roadmaps with strategic business outcomes.
- Define enterprise data and knowledge strategy across business domains and enterprise taxonomy, including knowledge graph, data governance with focus on ownership, metadata frameworks, business glossaries, data product orientation, interoperability and AI-enabling architecture.
- Shape AI governance and decision-intelligence strategy using autonomous enterprise concepts, including policies, guardrails, reference architectures and knowledge-based patterns for responsible AI adoption and enterprise knowledge reuse.
- Support SAP S/4HANA cloud migration strategy and evaluate the future SAP ecosystem, including SAP BTP, Integration Suite, Business Data Cloud, SAP Analytics Cloud and Datasphere.
- Drive architecture debt management, portfolio transparency and application rationalization through architecture principles, governance models, decision frameworks and LeanIX-based Enterprise Architecture Management.
- Align business architecture and process intelligence using Signavio to connect value chains, capabilities, processes, data strategy, knowledge flows and transformation roadmaps.
- Define operating models for data governance, architecture governance, cloud, integration, API management, AI governance and knowledge sharing.
- Act as trusted advisor to executive stakeholders and business domain leaders across product, sales, finance, logistics, customer care and shared services.
Ralph B.
Last position:
Senior Solution Architect Cloud, Data & AI at Sogeti Deutschland GmbH – Part of Capgemini
Assessed, structured, and managed complex tenders for Sogeti and as part of larger Capgemini proposals. Focused on analyzing challenging customer requirements, developing robust solution concepts, and translating technical, business, and commercial aspects into compelling proposal storylines. Working closely with delivery, sales, account, and proposal teams, I designed and assessed scalable, practical Quality Engineering solutions and prepared them for customer decisions. This included selecting suitable role profiles and right-shore staffing options, assessing available skills and capacity, and developing robust commercial pricing and effort estimates.
Particular focus on bid management and service proposal development (RfP-/Rfl analysis), solution design, presentation and management materials, and the business and technical assessment of customer requirements in the context of Quality Engineering & Testing and agentic AI-enabled test automation using modern quality assurance approaches.
SOGETI Projects:
- BMW: Developed a test strategy covering 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, an AI agent layer, and a hypercare concept.
- AIXTRON: SAP S/4HANA Cloud Migration Explore Phase, including QA assessment, a testable blueprint structure, staffing, and a scalable Sogeti delivery approach.
- Deutsche Glasfaser: Quality Engineering & Testing for DG Development Squads, including ServiceNow and Salesforce, test automation, and governance.
- ERGO: RfP and proposal support for Managed Service Test Data Provisioning, as well as a Jira/Atlassian implementation covering assessment, target vision, MVP, rollout, and governance.
- Münchener Rück: Proposal and solution design in the insurance sector, focused on test data provisioning, process analysis, compliance, and automation.
- BWI: Project and proposal work in the public sector and IT services, related to Quality Engineering, Test Factory, and digital transformation support.
- Rolls-Royce: Proposal and project support in the Sogeti context, focused on structured RfP analysis, solution design, and customer-focused proposal development.
Daryoosh D.
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
Ludo P.
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
Umut G.
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.
Uwe S.
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 L.
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
Discover over 15,000 top freelancers
Data Architects statistics
Aggregated from the professional profiles of matched freelancers.
Experience
21 years
Position duration
3.6 years
Positions per freelancer
15
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Information Technology, Manufacturing, Automotive
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
93%
Master's degree or higher
56%
Doctorate
7%
Certifications per freelancer
5
Most common languages
German, English, Spanish
Speak two or more languages
96%
Based on our profile pool as of 15 Nov 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this role in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Discover detailed Data Architects rate benchmarks:
Explore rate insightsAverage 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 15 Nov 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Data Architects 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 (91%)
- Manufacturing (57%)
- Automotive (53%)
- Banking and Finance (53%)
- Professional Services (53%)
- Transportation (43%)
- Telecommunication (40%)
- Retail (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
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 99 €, which corresponds to a daily rate of about 796 € based on an 8-hour working day.
Of the freelancers working as Data Architects in Germany, 93% hold at least a Bachelor's degree, 56% hold at least a Master's degree, and 7% hold a doctorate.
On average, freelancers working as Data Architects in Germany have 21 years of professional experience, with a single engagement typically lasting around 3.6 years.
The most common languages among freelancers working as Data Architects in Germany are German (100%), English (94%), and Spanish (11%).
The most common industries among freelancers working as Data Architects in Germany are Information Technology (91%), Manufacturing (57%), and Automotive (53%).
The most common business areas among freelancers working as Data Architects in Germany are Information Technology (100%), Business Intelligence (89%), and Project Management (75%).
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 
Munich Countries:
- Germany
- Switzerland
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FRATCH CEO
