Data Warehouse Experts in Nuremberg
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Meet FRATCH Experts in Nuremberg, who have recently used Data Warehouse
Vladimir Ergovic
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 Langheinrich
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 Hosseininia
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.
Leif Stolberg
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
Pawan Saxena
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 Khosla
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 Ndjenndja
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
Tim Safarowsky
Last position:
Freelance Business Intelligence Consultant at Self-employed
- Ongoing support on a Lucanet project in Hamburg (logistics/financial market)
- Advising on budgeting issues
- Advising on questions related to asset accounting
- Support in reporting
- Lucanet implementation for a client near Munich (retail/building materials)
- Support with initial setup
- Preparation of data imports from Excel
- Development of (SQL) interface to Navision data
- Ongoing support on a Lucanet project in Munich (pharma/medical)
- Data output in SQL Server
- Support and advice on setting up consolidation (legal)
- Ongoing support on a Lucanet project in Cologne (publishing)
- Preparation of Excel imports
- Support during initial setup (project restart)
- Ongoing support on a Lucanet project in Ludwigsburg (chemicals, printing inks, hobby paints)
- Connecting Lucanet to existing data warehouse solution (SQL)
- Ongoing support on a Lucanet project in Bad Staffelstein (solar industry)
- Connecting Lucanet to existing data warehouse solution (SQL)
- Integration of Lucanet reporting package
- Support and advice on setting up consolidation (legal & management)
- Ongoing support on a Lucanet project in Zeven (transport and logistics)
- Administration of existing Lucanet solution
- Integration of Lucanet reporting package
- Support and advice on setting up consolidation (legal & management)
- Support for planning, forecasting
- Lucanet implementation for a client in Luxembourg (retail)
- Installation and setup
- Support with initial setup
- Preparation of data imports Excel/DWH interface
- Lucanet implementation for a client in Nuremberg (manufacturing)
- Support with project restart
- Design for reporting and planning
- Setup of import packages
- Lucanet in-house consultant for an international software group focusing on M&A
- Consulting and support for the corporate holding and business units regarding implementation, rollout and operation of the Lucanet disclosure management solution
- Lucanet implementation for a client in Wassertrüdingen
- Database setup and configuration
- Connection of source systems with Lucanet interfaces
- Consolidated financial statements setup
- Support in the consolidation process
- Support in the reporting process
- Support of Lucanet for a client in Stuttgart
- Support in the consolidation process
- Support in the reporting process
- Support in the planning process
- Sparring partner for the specialist department
- Support of Lucanet for a client in Landau
- Implementation of cost center allocation in Lucanet
- Support in the consolidation process
- Lucanet carve-out support for a client in Waldstetten
- Database setup and configuration
- Design and implementation of BI software for a personnel service provider in Nuremberg
- Integration of 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 for an elevator company in Nuremberg
- Integration of 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 for a logistics company in Leipzig
- Integration 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 for a corporate group in Freilassing
- Integration 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 advice for creating a data warehouse
- Support in report creation in Power BI
- Support in transforming an existing DWH solution to SAP BW
- Analysis and documentation
- Ongoing consulting on processes
- Support in designing BW/SAC models
- Reporting in SAC
- Rebuilding a BI environment for an international company from Berlin (manufacturing/trade)
- Connecting SAP BO to new DWH (SSIS)
- Creation of tabular model cubes (SSAS)
- Creation of reports and KPIs
- User training
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: 3.3 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%
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 30 Aug 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it is
A data warehouse is a central store for analytics data. It combines records from ERP, CRM, finance, web, and operational systems so teams can query one trusted view. It is built for reporting, historical analysis, and decision support, not for day-to-day transaction processing.
Typical work
- Design fact and dimension models for dashboards and reporting
- Build ETL and ELT pipelines from source systems
- Set up data quality checks and lineage
- Optimize SQL queries and warehouse performance
- Support migration from legacy DWH or EDW setups
Common stack
Strong professionals work across platforms such as Snowflake, BigQuery, Amazon Redshift, Azure Synapse, and Teradata. They use SQL, dbt, Airflow, Python, and BI tools like Power BI or Tableau to shape, load, test, and serve clean data. They also know how to balance cost, speed, and governance.
When to bring in help
Companies bring in freelance expertise when reporting is slow, data definitions conflict, or a warehouse migration is blocked. They also need help when a new source system must be connected, a data mart must be added, or existing pipelines need redesign. In Nuremberg, this often fits teams that work with manufacturing, logistics, retail, and industrial data.
What strong professionals do
- Write clear SQL and model data for reuse
- Understand source-to-target mappings
- Handle incremental loads and late-arriving data
- Document business rules in plain language
- Work closely with analysts, data owners, and security teams
Good fit signals
A strong data warehouse specialist asks about source quality, load windows, retention rules, and who owns each metric. They can explain trade-offs between star schemas, snowflake schemas, and wide tables. They also know when a warehouse should stay simple and when it needs stronger governance, partitioning, or orchestration.
Frequently asked questions
Need clarity? These are the questions we hear most often about Data Warehouse.
A strong Data Warehouse brings together data from many systems so teams can analyze revenue, operations, customer behavior, and supply trends in one place. It is used for BI dashboards, finance reporting, performance tracking, and trend analysis. It is not meant for fast transaction handling.
A data warehouse stores curated, structured data that is ready for SQL analysis and reporting. A data lake usually keeps raw or semi-structured data and gives more freedom, but less built-in structure. Many companies use both, with the warehouse as the trusted reporting layer.
A DWH freelancer helps when reporting is unreliable, source systems are changing, or a migration is too large for the internal team. They are also useful when you need a new domain model, a clean data mart, or better pipeline testing. Short-term support can also help unblock a specific release.
A solid Data Warehouse specialist usually works well with SQL, dimensional modeling, ETL or ELT, and orchestration tools. Python, dbt, Airflow, and cloud platforms such as Snowflake, BigQuery, or Redshift are common adjacent skills. Business analysis and data governance matter too.
A data warehouse project needs someone who has shipped real pipelines and models, not just read about them. Simple reporting fixes may need only focused help, while migrations and multi-source setups need deeper platform and modeling experience. The more source systems and business rules involved, the more important proven practice becomes.
For EDW work, look for clear examples of schema design, pipeline reliability, and performance tuning. Good professionals can explain how they handled bad source data, changing definitions, and access control. Ask for a walkthrough of a past model, not just a tool list.
A data warehouse specialist can usually work well remotely because most tasks are design, SQL, and pipeline work. On-site time can help early in the project when business rules are unclear or many stakeholders need to agree on definitions. For teams in Nuremberg, a hybrid setup is often practical.
A strong data warehouse implementation is easy to query, easy to change, and well documented. Tables have clear ownership, loads are monitored, and key metrics match across reports. If analysts trust the numbers and the team can explain where each value comes from, the setup is on the right track.
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 850 € 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
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
