Data Warehouse Experts in Nuremberg
matched in minutesHire experts who design analytical data models, build reliable ETL and ELT pipelines, and connect cloud or on-premises platforms such as Snowflake, BigQuery, Amazon Redshift, and Microsoft Fabric. FRATCH precisely matches you with vetted, available freelancers who fit your project.
Meet FRATCH Experts in Nuremberg, who have recently used Data Warehouse
Leif S.
Last position:
Software Architect at QualityMinds GmbH
- Lead software architect and technical team lead for a new logistics platform for load carrier trade
- Core design of software architecture using arc42 spanning frontend, backend, delivery strategies and cloud native infrastructure with Domain Driven Design and Hexagonal Architecture
- Evaluation of initial business requirements and software development roadmap
- Technical team lead in a Scrum team of 9 people
- Introduced and strengthened AI-assisted (JetBrains AI & GitHub Copilot) and collaborative code development strategies to speed up feature development
Vladimir E.
Last position:
Technical Project Manager / Freelancer at Deutsche Bank
- Engaged within the Information and Security Management division for a Proof of Concept (PoC) project focused on developing a Client Security Portal.
- Managed project resources across the UK, India, and Germany.
- Architected and deployed the PoC solution leveraging a modern Java stack, Google Cloud Platform (GCP) with Kubernetes, and Active Directory (Entra ID) for authentication.
- Implemented OAuth 2.0 for authorization.
- Ensured DORA alignment according to Deutsche Bank security rules and regulatory preparation.
Peter L.
Last position:
Zoho Consulting and Development at Zuperstars mit Z wie Zoho
- Consulting on functional topics and their feasibility with Zoho technologies
- Implementing solutions based on Zoho
- Integrating Zoho solutions with third-party systems
- Performing data migrations
- Training and support
Elnazossadat H.
Last position:
Data Analyst at Siemens Healthineers
- Developed KPI dashboards using Power BI and DAX for 4+ business units, improving reporting transparency and strategic decision support.
- Migrated enterprise finance data views into dbt models, implementing modular SQL transformations, version-controlled data pipelines, and automated documentation to create a scalable analytics layer.
- Built dimensional data models in Snowflake for enterprise finance data, enabling scalable forecasting and supporting executive decision-making.
- Designed end-to-end ETL/ELT pipelines using Snowflake and SAP HANA, integrating data from 3+ enterprise systems.
- Automated monthly reporting workflows using SQL and Power BI, delivering strong business impact by reducing manual effort by 80%.
- Collaborated with finance stakeholders to translate business requirements into analytical data models, supporting strategic decision-making cycles.
- Delivered ad-hoc financial reports using Power BI, reducing turnaround time by 60%.
- Implemented data validation logic in SQL, resolving 95% of recurring data quality issues.
Tim S.
Last position:
Freelance Business Intelligence Consultant at Self-employed
- Ongoing support for a Lucanet project in Hamburg (logistics/financial market)
- Consulting on budgeting topics
- Consulting on fixed asset accounting issues
- Support with analyses
- Implementation of Lucanet at a customer near Munich (retail/building materials)
- Support with the initial setup
- Preparation of Excel data imports
- Development of an SQL interface to Navision data
- Ongoing support for a Lucanet project in Munich (pharmaceuticals/medical)
- Data output to SQL Server
- Support and consulting in setting up legal consolidation
- Ongoing support for a Lucanet project in Cologne (publishing)
- Preparation of Excel imports
- Support with the initial setup (project restart)
- Ongoing support for a Lucanet project in Ludwigsburg (chemicals, printing inks, hobby paints)
- Connecting Lucanet to an existing data warehouse solution (SQL)
- Ongoing support for a Lucanet project in Bad Staffelstein (solar industry)
- Connecting Lucanet to an existing data warehouse solution (SQL)
- Connecting the Lucanet Reporting Package
- Support and consulting in setting up legal and management consolidation
- Ongoing support for a Lucanet project in Zeven (transport and logistics)
- Administration of the existing Lucanet solution
- Connecting the Lucanet Reporting Package
- Support and consulting in setting up legal and management consolidation
- Support with planning and forecasting
- Implementation of Lucanet at a customer in Luxembourg (retail)
- Installation and setup
- Support with the initial setup
- Preparation of Excel/DWH interface data imports
- Implementation of Lucanet at a customer in Nuremberg (manufacturing)
- Support with the project restart
- Design of reporting and planning
- Setup of import packages
- Lucanet in-house consultant at an international software group with a focus on M&A
- Consulting and support for the group holding company and business units regarding the implementation, rollout and operation of the Lucanet Disclosure Management solution
- Implementation of Lucanet at a customer in Wassertrüdingen
- Database setup and configuration
- Connecting source systems using Lucanet interfaces
- Preparation of consolidated financial statements
- Support with the consolidation process
- Support with the reporting process
- Support for Lucanet at a customer in Stuttgart
- Support with the consolidation process
- Support with the reporting process
- Support with the planning process
- Sparring partner for the specialist department
- Support for Lucanet at a customer in Landau
- Implementation of cost center allocation in Lucanet
- Support with the consolidation process
- Support for a Lucanet carve-out for a customer in Waldstetten
- Database setup and configuration
- Design and implementation of BI software at a staffing services provider in Nuremberg
- Connecting various source systems
- Development of data warehouse and ETL processes
- Creation of several cubes and data marts
- Ongoing support and further development
- Based on: Cubeware Importer, SQL Server, TM1
- Design and implementation of BI software at an elevator company in Nuremberg
- Connection to Navision BC
- Development of data warehouse and ETL processes
- Creation of several cubes and data marts
- Based on: Cubeware Importer, SQL Server
- Design and implementation of BI software at a logistics company in Leipzig
- Connection of various source data
- Development of data warehouse and ETL processes
- Creation of several cubes and data marts
- Based on: Cubeware Importer, SQL Server, TM1
- Design and implementation of BI software at a corporate group in Freilassing
- Connection of various source data
- Development of data warehouse and ETL processes
- Based on: Cubeware Importer, SQL Server, TM1
- Design and implementation of a new reporting environment based on SQL Server and Power BI
- Best practice consulting for the creation of a data warehouse
- Support with report creation in Power BI
- Support with transforming an existing DWH solution to SAP BW
- Analysis and documentation
- Ongoing consulting on processes
- Support with designing BW/SAC models
- Reporting in SAC
- Rebuilding the BI environment at an international company from Berlin (manufacturing/retail)
- Connecting SAP BO to the new DWH (SSIS)
- Creation of tabular model cubes (SSAS)
- Creation of reports and KPIs
- User training
Pawan S.
Last position:
CAPTCHA Recognition using CRNN
- Built a CRNN model with VGG16 and BiLSTM backbone for text-based CAPTCHA recognition
- Achieved 9.37% character error rate and 68.36% sequence accuracy on validation data
- Expanded data augmentation pipeline with distortions, noise injection, and clutter to improve robustness
- Conducted detailed error analysis on confusable characters (O, Q, D) and proposed error-specific augmentation
- Tech Stack: Python, TensorFlow/Keras, OpenCV, NumPy, Matplotlib
Ekaansh K.
Last position:
Master thesis - LLM powered RAG System at Friedrich-Alexander-Universität Erlangen-Nürnberg
- Developed a RAG system to automate student queries with 96% accuracy, built using FastAPI and LangChain and deployed on the university server with Docker.
- Evaluated performance using RAGAS, comparing LLMs (Llama3.3, Llama3.1, GPT-4o-mini), vector embeddings, and various retrieval techniques within the RAG pipeline.
- Technical Skills: Python, FastAPI, Docker, AWS, LangChain, LangSmith, NLP, HTML, CSS
Guino N.
Last position:
Senior Data Engineer at Infomotion
- Built a data analytics platform for Karl Storz
- Developed all ETL processes in a generic way
- Prepared and supplied data in Databricks Delta tables for use in Databricks Machine Learning
- Technologies & Tools: Azure Data Factory, CI/CD pipeline with GitHub DevOps, Python, Azure Databricks (Unity Catalog), T-SQL
Discover over 15,000 top freelancers
Statistics of experts using Data Warehouse
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 22 years)
Position duration
3.1 years (Germany: 3.2 years)
Positions per freelancer
7 (Germany: 13)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Banking and Finance, Healthcare
Certification focus areas
Business Intelligence, Information Technology, Project Management
Bachelor's degree or higher
88% (Germany: 89%)
Master's degree or higher
63% (Germany: 57%)
Doctorate
13% (Germany: 10%)
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 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 Nuremberg 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 Nuremberg using Data Warehouse
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 Warehouse 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 (100%)
- Banking and Finance (75%)
- Healthcare (75%)
- Automotive (38%)
- Education (38%)
- Transportation (38%)
- Professional Services (38%)
- Retail (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Purpose
A data warehouse consolidates structured information from business systems into a reliable foundation for reporting, analytics, and decision-making. It separates analytical workloads from operational applications and gives teams consistent definitions for revenue, customers, products, and performance.
Core architecture
Experts design layers for ingestion, storage, transformation, serving, and governance. They choose between cloud, on-premises, and hybrid architectures, then define dimensional models, data marts, schemas, partitioning, and access patterns that support dependable analysis.
Ecosystem
The work spans source systems, orchestration, transformation, storage, and visualization. Common tools and platforms include:
- Snowflake, Google BigQuery, Amazon Redshift, and Microsoft Fabric
- dbt, Apache Airflow, Fivetran, and cloud-native integration services
- Power BI, Tableau, Looker, and semantic modeling layers
Project signals
Freelance expertise helps when reporting is slow, definitions conflict, or a company is moving from spreadsheets and operational databases to governed analytics. It is also valuable during cloud migrations, platform selection, merger integration, and the launch of self-service reporting. In Nuremberg, specialists may need to align remote delivery with on-site stakeholders across manufacturing, logistics, healthcare, and services.
Delivery skills
Strong professionals translate business questions into maintainable data products. They profile source data, manage incremental loads, handle schema changes, document lineage, test transformations, monitor freshness, and control access. They also understand SQL, data quality, metadata, backup strategies, and the trade-offs between batch and near-real-time processing.
Quality checks
Look for a clear modeling approach, traceable transformations, and practical plans for ownership after handover. A capable specialist explains assumptions, validates outputs with business users, and builds observability into the pipeline rather than treating it as an afterthought. They communicate clearly in the working language and leave behind documentation, tests, and repeatable deployment processes.
Frequently asked questions
Need clarity? These are the questions we hear most often about Data Warehouse.
A Data Warehouse stores integrated, historical business data for reporting, dashboards, analytics, and controlled decision-making. It brings information from systems such as ERP, CRM, finance, and production into a structure that is easier to query consistently.
A Data Warehouse usually stores curated, structured data prepared for reliable analysis, while a data lake can retain raw structured, semi-structured, and unstructured information. Many modern architectures use both, with the choice depending on governance, flexibility, users, and workload requirements.
A strong Data Warehouse professional often combines advanced SQL with dimensional modeling, ETL or ELT design, orchestration, cloud infrastructure, data governance, and testing. Experience with dbt, Apache Airflow, BI tools, APIs, and security controls can also be important.
The right Data Warehouse experience depends on the scope, source-system complexity, delivery deadline, and existing team. A migration or platform redesign needs someone who can shape architecture and manage risk, while a focused reporting improvement may need a specialist in modeling, pipelines, or performance tuning.
Yes, much Data Warehouse work can be delivered remotely through shared repositories, documentation, ticketing, and secure cloud access. On-site workshops in Nuremberg can still help with stakeholder discovery, source-system access, and decisions that require close collaboration.
Ask a Data Warehouse freelancer to explain a comparable architecture, including data modeling, testing, monitoring, lineage, and failure handling. Strong answers connect technical choices to business use cases and show how the solution remains understandable and maintainable after delivery.
A Data Warehouse project may produce an architecture design, source mapping, dimensional model, ingestion pipelines, transformation code, documentation, dashboards, and operational monitoring. The deliverables should also cover data quality rules, access permissions, deployment processes, and ownership.
Bring in a Data Warehouse freelancer when internal teams lack specialist capacity for a migration, urgent reporting initiative, platform evaluation, or pipeline redesign. A focused professional can also review an existing environment, identify reliability risks, and transfer practical knowledge to the permanent team.
The average hourly rate of freelancers in Nuremberg, Germany who have used Data Warehouse in their recent projects is 106 €, which corresponds to a daily rate of about 849 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Data Warehouse in their recent projects, 88% hold at least a Bachelor's degree, 63% hold at least a Master's degree, and 13% hold a doctorate.
On average, freelancers in Nuremberg, Germany who have used Data Warehouse in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 3.1 years.
The most common languages among freelancers in Nuremberg, Germany who have used Data Warehouse in their recent projects are German (100%), English (100%), and French (25%).
The most common industries among freelancers in Nuremberg, Germany who have used Data Warehouse in their recent projects are Information Technology (100%), Banking and Finance (75%), and Healthcare (75%).
The most common business areas among freelancers in Nuremberg, Germany who have used Data Warehouse in their recent projects are Business Intelligence (100%), Information Technology (100%), and Product Development (63%).
Main locations of FRATCH Experts, who have recently used Data Warehouse
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 
Dusseldorf 
Essen 
Hanover Request a free demo
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Philipp Thomaschewski
FRATCH CEO
