Data Modeling Expert in Frankfurt
for clear, reliable data foundations, matched in minutes with the power of AIHire experts who design conceptual, logical and physical data models, align relational and dimensional structures, and document data flows across modern platforms. FRATCH connects you with vetted, available freelancers through fast, precise AI matching.
Meet FRATCH Experts in Frankfurt, who have recently used Data Modeling
Justina K.
Last position:
Freelance Consultant for Change & Data Transformation at Freelance Fast Data Consulting
Project, Strategic Consulting – building the Data Strategy and Data Governance Policy for the German branch, client (private bank Julius Bär, headquarters Zurich), March 2026 – present
- Design and negotiation of the data strategy with key stakeholders, including obtaining board sign-off (strategic consulting) – in this context, regulatory advice on data regulations in the EU and specifically for Germany. The data strategy includes: Data Lifecycle Management: data capture, data storage, data usage, data retention policy, data quality incident management
- Definition of milestones and technical feasibility for implementing TOM for the data strategy, data quality checks, metrics, and a metadata inventory to ensure the bank’s compliance with DORA, BCBS239, and MaRisk requirements.
Core project data change, client: (ING Bank, Frankfurt am Main), March – December 2025
- Concept development and solution design for new end-to-end processes including technical interfaces
- Definition of synchronization logic and data flows between legacy and target systems (decommissioning of legacy systems)
- Analysis and validation of data models
- Stakeholder communication with product owners, feature engineers, UX designers, and operational teams for decision-making
- Analytics and impact assessments, e.g. to assess downstream effects and regulatory requirements
- Documentation and comments on technical and business requirements to support implementation in agile squads
Project digitalization of a user group, client: (ING Bank, Frankfurt am Main), as Interim Product Owner, Jan 2025 – present
- Co-shaping key decisions on data architecture and process logic in the context of historized data and user login functionality
- Development of business solution concepts for migration to the target system, including system integration and data flows
- Support with analytics and impact analyses, especially regarding the ability to provide information to law enforcement authorities
- Active coordination with stakeholders from different squads to support decision-making and ensure regulatory requirements are met
- Creation of test scenarios for operational teams and backend systems in the area of API management using Postman and Bruno.
Torsten F.
Last position:
Data Analyst, Requirements Manager at Isabellenhütte Heusler GmbH
Analysis of the existing reporting platform including processes and governance topics with stakeholders from sales and marketing.
Detailed analysis and evaluation of client-defined requirements for existing reporting and new dashboards.
Supporting stakeholders in managing sales processes and early detection of KPI trends.
Use of Microsoft Power BI as central analysis and reporting platform.
Developing a proposal for the necessary evolution of processes and the Power BI platform.
Gathering current business processes and defining company-wide KPIs in coordination with stakeholders.
Analysis and inventory of the client's Power BI platform.
Analysis of processes and data governance.
Recording and documenting current business processes.
Developing recommendations for process and reporting platform improvements.
Designing and implementing dashboards in Power BI.
Defining company-wide KPIs and aligning them with stakeholders.
Microsoft Power BI.
Data analytics.
KPI definition and reporting.
Dashboard design and data visualization.
Stakeholder management and requirements management.
Monika T.
Last position:
Senior ETL Lead at Takeda GmbH
- Led design, development, and deployment of data solutions supporting a major pharma acquisition for Takeda Pharmaceutical Company, delivering transparency reporting systems across Azure,Databricks (Python and Shell Scripting) platforms.
- Owned,Designed and developed scalable ELT pipelines to process Customer and Product data using Azure, complex SQL, Databricks, and shell scripting, enabling efficient data integration and processing across multiple sources including job orchestration and workflow automation.
- Implemented performance optimization techniques (query tuning, parallelism, workload optimization), improving system efficiency and processing time.
- Applied strong analytical and problem-solving skills to assess technical solutions and support business requirements for compliance and transparency reporting.
- Designed scalable data foundations suitable for downstream analytics and AI workloads.
- Led data quality initiatives by assessing multiple source data, defining quality metrics, and establishing processes for monitoring and continuous improvement.
Benedikt R.
Last position:
Power BI developer at Mechanical Engineering (SME 500 emp.)
- KPI dashboards for inventory and goods received quality control & testing ETL, dataset, dataflows and report development, complex DAX solutions
Data sources: Dataverse, RDB, Excel
Tools: ETL, data modeling, data flows, Power Query, M, Power BI, complex DAX
- Capacity: 25%
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.
Jana C.
Last position:
Freelance Business Intelligence Consultant at Superprof Germany & Upwork
- Design an interactive Tableau dashboard to analyze historical aviation accidents using data from the Federal Bureau of Aircraft Accident Investigation
- Develop visualizations to provide actionable insights to improve aviation safety measures employing data modeling and transformation techniques
- Develop a Power BI dashboard to monitor sales KPIs and product performance integrating data from multiple sources
- Design a star schema data model and implement advanced DAX measures for high-performance and dynamic reporting
- Design a comprehensive BI architecture solution focusing on ETL pipelines, data integration, and data governance
- Recommend Power BI as the central tool and create a security-compliant implementation roadmap
Silvia F.
Last position:
Agile PM at Puma SE
- Manage and oversee various software development projects between product management and agile dev teams of external service providers
- Communicate with all stakeholders
- Promote transparency and focus on project topics
- Facilitate alignments between business units and external partners
- Support product managers and product owners in preparing and managing requirements in workshops and tools
- Use short feedback loops to optimize agile collaboration
- Support hybrid and agile collaboration
Vladimir F.
Last position:
IT Consultant at ITZBund
- ITSM consulting, analysis and optimization of IT capacity with BMC TSCO / BMC Helix
- Drafting "Governance guidelines for operational capacity management"
Eric B.
Last position:
Quality Assurance Lead (QSV) at Federal Employment Agency
Supported the International Web Presence project of the Federal Employment Agency (IntWeb) in quality management, taking on responsibility for the quality of processes and project deliverables while adhering to BA standards. The project's main goals are to give professionals abroad a quick overview of their chances to move to Germany and to enable them to take the necessary steps in a consistently digital way.
Set the fundamental guidelines using the QA handbook
Summarized test results in QA reports for PLA
Analyzed project outcomes for improvement opportunities
Quality management of requirements analysis (especially processes, methods and tools)
Ensured compliance with SERA guidelines
Created a cross-project test concept
Agreed on sprint completion reports
Conducted formal reviews of deliverables according to guidelines and/or project plan
Acted as contact person for internal audit and external audits by auditors or the Federal Audit Office (BRH)
Technologies: JIRA, Confluence, MS Office, GitLab, Kubernetes
Polina S.
Last position:
Data Migration Lead – Process Automation, Data Engineering & Reporting at Large Public-Sector Bank
Configured and automated data extracts from Oracle databases, achieving 100% data accuracy in a critical migration project, significantly reducing manual errors and accelerating the migration timeline.
Designed and implemented interfaces with Order Management Systems (OMS), enabling seamless and automated data exchange and improving operational efficiency through faster, error-free order processing across business units.
Developed and deployed data extraction workflows to support regulatory compliance and customer reporting, ensuring timely delivery of key reports, reducing manual effort, and increasing customer satisfaction.
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.
Ashkan Z.
Last position:
Microsoft Azure Senior Data Engineer / Senior Data Scientist at Vattenfall Europe
- Advising on the use of analytics and BI tools and services in the Microsoft Azure stack (e.g. MS Fabric, Synapse Workspaces and dedicated SQL pools, SQL Database, PostgreSQL, Snowflake, Databricks, Data Factory, SSIS, Analysis Services, Function Apps, Power BI, ML)
- Independently designing analytics solutions with Python, SQL, etc.
- Designing and implementing ETLs and data pipelines
- Creating and maintaining APIs
- Independently applying CI/CD, testing, and version control
- Data modeling
- Model development and optimization
- Anomaly detection with AI
- Predictive analytics
Used technologies:
- Snowflake
- Fabric
- Azure Synapse Analytics
- Azure DataFactory
- Azure Data Lake
- Azure DevOps
- Databricks
- Spark
- CI/CD
- SQL Database
- Python
- Power Platform
Valentin O.
Last position:
Network Architect at IT Service Provider - Public Sector
- Designed a network management strategy focused on NetDevOps principles and model-driven telemetry using YANG data models
- Conducted NETCONF/YANG workshops for L2VPN/L3VPN services over SRv6
- Automated configuration deployment in the testing environment with Ansible
- Developed end-to-end service measurement concepts with IPSLA and the Telegraf-Prometheus-Grafana stack
- Created the dual-stack architecture design (router + switch + firewall) including a detailed test plan; planned, executed, and documented acceptance tests for the management network
- Performed BSI IT baseline protection checks according to the IT-Grundschutz catalog (needs assessment, modeling, risk analysis, deriving measures)
- Protocols: SRv6, IPv6, MPLS, BGP, ISIS, OSPF, NETCONF/YANG, model-driven telemetry, IPSLA
- Systems: Cisco Crosswork Network Controller, SolarWinds Orion, Grafana, InfluxDB, Telegraf, Ansible, Git
- Components: Cisco NCS router series, Cisco Catalyst switch series, Cisco Firepower firewall series
Zahra D.
Last position:
Data and Process Analyst in Healthcare at Ministry of Health and Medical Education
- Optimized the patient journey through big data analysis and cross-functional collaboration
- Regionalized NICU centers with 86% coverage using mathematical models
- Developed patient flow and geoprocessing models with Python and ArcGIS, resulting in an 18% increase in efficiency
- Built simulation models to optimize bed utilization and reduce waiting times with Rockwell Arena
- Developed analytical dashboards in collaboration with clinical experts
- Implemented machine learning algorithms for birth predictions and cross-functional prescription analyses
Lutz H.
Last position:
Developer for Oracle Forms, PL/SQL, Java at AIG Europe S.A.
- Development and implementation of backend components with PL/SQL and Oracle Forms 12c. Adaptation and further development of the policy administration system. Technical consulting in UI design with a focus on integrating existing Oracle Forms and the requirements of the BIPRO framework.
- The project takes place in the technical environment of BIPRO, SQL databases and Oracle Forms applications. The assigned work includes backend development and technical further development in the above project with the following tasks:
- Development and implementation of backend components with PL/SQL and Oracle Forms 12c to technically map the business processes and ensure a stable and efficient system architecture
- Adaptation and further development of the policy administration system to ensure system functionality in line with the requirements of the new broker communication program
- Analysis of the existing system to identify and avoid errors and technical problems during implementation, in order to enable a smooth transition to the new system
- Carrying out patching and further development of existing Oracle and Oracle Forms applications to ensure compatibility and security of the systems in use
- Technical consulting in UI design with a focus on integrating existing Oracle Forms and the requirements of the BIPRO framework.
Label: PL/SQL, Java, Oracle RDBMS and Oracle Forms
Discover over 15,000 top freelancers
Statistics of experts using Data Modeling
Aggregated from the professional profiles of matched freelancers.
Experience
21 years (Germany: 18 years)
Position duration
2.3 years (Germany: 3 years)
Positions per freelancer
12
Top business areas
Information Technology, Project Management, Business Intelligence
Top industries
Information Technology, Banking and Finance, Telecommunication
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
96% (Germany: 92%)
Master's degree or higher
65% (Germany: 63%)
Doctorate
12% (Germany: 10%)
Certifications per freelancer
4 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
94% (Germany: 97%)
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 Frankfurt 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 Frankfurt using Data Modeling
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.
Data Modeling 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 (73%)
- Banking and Finance (67%)
- Telecommunication (39%)
- Professional Services (36%)
- Government and Administration (36%)
- Energy (27%)
- Insurance (27%)
- Automotive (24%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Data Modeling Covers
Data modeling defines how business information is structured, related and governed. It turns unclear requirements into conceptual, logical and physical models that guide databases, applications, analytics and integration work. The practice covers entities, attributes, relationships, keys, constraints and business rules.
Models for Business Systems
A strong model creates a shared view of information before teams build or change a system. Experts translate processes into structures that support reliable transactions, reporting and long-term maintenance.
- Relational models for operational databases
- Dimensional models for reporting and analytics
- Domain models for applications and services
- Canonical models for integration across systems
Ecosystem and Tooling
Data Modeling work connects closely with SQL, database design and data architecture. Specialists may use ER diagram tools, SQL workbenches, catalogues and schema management workflows, while working with systems such as PostgreSQL, Microsoft SQL Server, Oracle Database, Snowflake or BigQuery. Knowledge of normalization, denormalization, star schemas and data warehouses is often important.
When Companies Need Specialists
Companies usually bring in freelance expertise when a new platform must be designed, existing data has become inconsistent, or several systems need a common structure. Frankfurt organizations may also value professionals who can work smoothly with distributed teams and communicate clearly in English and German where required.
- Rework a fragile or undocumented database structure
- Prepare a warehouse or lakehouse model for analytics
- Map data during system integration or migration
- Establish naming, ownership and documentation standards
What Good Deliverables Include
Quality work produces more than an attractive diagram. It includes documented assumptions, definitions, relationships, constraints and lineage, plus a clear link between business terms and implementation. Strong professionals validate models with domain teams, test them against real queries and explain trade-offs between consistency, performance and flexibility.
Choosing the Right Professional
Look for evidence of models delivered in environments similar to yours, not only familiarity with diagramming software. Ask how the professional handles changing requirements, legacy data, slowly changing dimensions, data quality and access rules. Experience with SQL, APIs, ETL or ELT, master data and governance can make collaboration more effective, especially when the model must serve both applications and analytics.
Frequently asked questions
Key details about Data Modeling, drawn from the questions we get asked most.
Data Modeling is used to describe the structure, meaning and relationships of information before or during system development. It supports database design, application integration, reporting, analytics, migrations and data governance. A clear model helps teams avoid duplication and interpret business data consistently.
Data Modeling focuses on the structure and relationships of data, while data architecture covers the wider landscape of platforms, flows, storage and governance. The two disciplines overlap, but a model is usually a more detailed representation of a specific domain or system.
Data Modeling is stronger when combined with SQL, database performance, ETL or ELT, data warehousing and data quality practices. Depending on the project, experience with APIs, master data, metadata catalogues, cloud storage and access governance is also valuable.
Data Modeling assignments vary widely in scope, from documenting one application to defining structures across an enterprise. Choose a professional based on experience with your data domains, systems and delivery stage rather than a generic seniority label. A short discovery phase can reveal the right level of involvement.
Data Modeling is well suited to remote collaboration because workshops, model reviews and documentation can be handled online. On-site sessions in Frankfurt may still help when domain knowledge is difficult to access or stakeholders need intensive alignment. Clear ownership of definitions and decisions is essential in either setup.
Data Modeling deliverables commonly include conceptual, logical or physical diagrams, a data dictionary, relationship definitions and implementation guidance. Depending on the brief, they may also cover lineage, transformation rules, migration mappings and validation against representative queries.
Data Modeling quality is visible in models that are understandable, consistent and useful for real decisions. Review how the professional explains assumptions, handles conflicting requirements, tests the model with stakeholders and connects business terms to database structures. Good documentation is as important as the diagram itself.
Data Modeling remains relevant in cloud warehouses, lakehouses and distributed data systems, even when storage is flexible. The approach may use dimensional, wide, normalized or domain-oriented structures depending on query patterns and governance needs. The professional should explain why a chosen model fits the platform and its users.
The average hourly rate of freelancers in Frankfurt, Germany who have used Data Modeling in their recent projects is 102 €, which corresponds to a daily rate of about 813 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Data Modeling in their recent projects, 96% hold at least a Bachelor's degree, 65% hold at least a Master's degree, and 12% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Data Modeling in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Frankfurt, Germany who have used Data Modeling in their recent projects are German (100%), English (91%), and French (24%).
The most common industries among freelancers in Frankfurt, Germany who have used Data Modeling in their recent projects are Information Technology (73%), Banking and Finance (67%), and Telecommunication (39%).
The most common business areas among freelancers in Frankfurt, Germany who have used Data Modeling in their recent projects are Information Technology (91%), Project Management (82%), and Business Intelligence (76%).
Main locations of FRATCH Experts, who have recently used Data Modeling
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.
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Munich 
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Dusseldorf 
Leipzig 
Essen 
Nuremberg Request a free demo
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FRATCH CEO
