ETL Experts in Nuremberg
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Meet FRATCH Experts in Nuremberg, who have recently used ETL
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
Michael Fecher
Last position:
Freelancer, Solution Architect at Schufa AG
- Helped to design the AWS infrastructure, integrated services and backend architecture for use cases of an on-premise solution and partial migrations to AWS with fast response times
- Implemented automated AWS integration test suites
- Implemented mission-critical components and delivered them before the deadline in a production-ready state with operation and monitoring concepts
- This 2-month subproject was about building a data-intense pipeline (5 TB) to be enriched continuously with data
- Designed and implemented reusable AWS CDK constructs to be used across the company’s teams to enable faster onboarding with AWS
- Coached on AWS topics, distributed software patterns, security, domain-driven design, agile collaboration and documentation to improve performance and collaboration
- Technologies: AWS, GitHub Actions, ETL, monitoring, operations, TypeScript, Python, AWS CDK, CloudFormation, Java, Docker, AWS ECS, AWS Lambda, serverless, Jenkins, DevOps principles
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.
Arun Sai Thunga
Last position:
AI-Backend Developer Intern at Calvergy UA
- Integrated complex AI-based energy system models into the frontend framework, enabling the visualization of insights for 6+ key clients and maximizing energy utilization.
- Maximized energy efficiency and utilization by architecting the seamless data flow between AI models and the user interface for rapid, actionable reporting.
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
Vasuraj Bhatia
Last position:
Cloud Data Analyst at Bhatia Reply
- Analyzed 50K+ customer records using SQL and Python in a cloud services firm, identifying trends
- Designed interactive Tableau dashboards for sales and marketing stakeholders, reducing report
- Developed ARIMA and AutoARIMA time series models to forecast AWS resource utilization, cutting
- Automated ETL pipelines with Python, improving workflow efficiency by 20% for scalable data
- Collaborated with DevOps teams to deploy 3 machine learning models in production using Docker
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 ETL
Aggregated from the professional profiles of matched freelancers.
Experience
15 years (Germany: 17 years)
Position duration
2.3 years (Germany: 5.2 years)
Positions per freelancer
8 (Germany: 11)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Business Intelligence, Information Technology, Product Development
Bachelor's degree or higher
100% (Germany: 95%)
Master's degree or higher
70% (Germany: 66%)
Doctorate
10% (Germany: 11%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 96%)
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 ETL
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
ETL work
ETL stands for extract, transform, load. It moves data from apps, files, APIs, and databases into a warehouse, lake, or reporting layer. Strong ETL work keeps records consistent, traceable, and ready for analysis.
Common projects
- Batch pipelines for finance, sales, operations, or supply chain data
- Data cleansing, mapping, deduplication, and enrichment
- Warehouse loads for Power BI, Tableau, and similar reporting tools
- Rebuilds from brittle scripts to maintainable pipeline flows
Tooling stack
ETL specialists often work with tools such as Informatica, Talend, SSIS, Pentaho, dbt, Airflow, and cloud services from AWS, Azure, or Google Cloud. They also handle SQL, stored procedures, file formats, and orchestration between source and target systems.
What strong experts do
A good ETL expert thinks about schema changes, data quality rules, failure handling, retries, and lineage. They document transformations clearly so business teams and technical teams can trust the same numbers. They also keep an eye on performance when datasets grow.
When to bring one in
Companies usually hire freelance ETL experts when feeds break, loads slow down, or a new source must be integrated quickly. In Nuremberg, this is common when local manufacturing, logistics, and enterprise teams need clean operational data without pausing ongoing work.
What to look for
Look for specialists who can read source schemas, write clear SQL, debug failed jobs, and explain transformation logic in plain language. Remote work is often enough, but on-site sessions in Nuremberg can help when teams need to align on source systems, business rules, and release timing.
Frequently asked questions
Everything clients usually want to know about ETL, in one place.
ETL extracts data from source systems, transforms it into a usable shape, and loads it into a warehouse, lake, or reporting store. It is used when raw operational data needs cleaning, joining, or standardizing before teams can rely on it. Good ETL work turns scattered data into something stable and queryable.
ETL transforms data before it reaches the target, while ELT loads first and transforms later inside the destination system. ETL is often chosen when business rules, validation, or privacy handling should happen before the load. ELT is common when the target platform has strong processing power and teams want to keep raw data longer.
A strong ETL specialist often knows SQL, workflow orchestration, and one or more integration tools such as Informatica, Talend, SSIS, Pentaho, or Airflow. Cloud services in AWS, Azure, or Google Cloud are also common when pipelines run in managed environments. The exact stack matters less than the ability to move data safely and explain the logic.
ETL work goes better with solid SQL, data modeling, and debugging skills. Familiarity with source APIs, file handling, warehouse design, and basic scripting helps a lot too. For many projects, communication with analysts and business teams is just as important as the technical setup.
A ETL project can need anything from a specialist for one broken pipeline to a more experienced professional for a full redesign. Simple data moves may only need clean SQL and good habits, while complex integrations need someone who can handle lineage, scheduling, and recovery. The harder the source systems and rules, the more senior the expert should be.
If loads fail often, source data changes without warning, or reporting teams keep fixing numbers by hand, it is time for ETL help. Other signs are unclear transformation rules, slow batch windows, or too many scripts owned by one person. Freelance support is useful when you need focused delivery without a long hiring cycle.
Most ETL work can be done remotely because the key tasks are analysis, coding, testing, and documentation. On-site time in Nuremberg can still help when access to internal systems is sensitive or when business and technical teams need to agree on source definitions. A mixed setup often works best for complex migrations.
Look for a ETL specialist who can explain transformations clearly, handle edge cases, and show how failures are detected and recovered. Good signs are clean SQL, thoughtful naming, solid documentation, and care for data quality and lineage. Ask how they test loads, manage schema changes, and keep business users confident in the output.
The average hourly rate of freelancers in Nuremberg, Germany who have used ETL in their recent projects is 93 €, which corresponds to a daily rate of about 743 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used ETL in their recent projects, 100% hold at least a Bachelor's degree, 70% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers in Nuremberg, Germany who have used ETL in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Nuremberg, Germany who have used ETL in their recent projects are German (100%), English (100%), and French (20%).
The most common industries among freelancers in Nuremberg, Germany who have used ETL in their recent projects are Information Technology (100%), Banking and Finance (80%), and Automotive (70%).
The most common business areas among freelancers in Nuremberg, Germany who have used ETL in their recent projects are Business Intelligence (100%), Information Technology (100%), and Product Development (80%).
Main locations of FRATCH Experts, who have recently used ETL
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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