Jupyter Experts in Frankfurt
in minutes from 15,000 CVs with vetted specialists and AI matching.Hire experts who turn Jupyter notebooks into clean analysis, reproducible research, and shareable data workflows. They work with JupyterLab, notebook extensions, Python kernels, and collaborative review setups, with fast and precise matching to vetted, available freelancers.
Meet FRATCH Experts in Frankfurt, who have recently used Jupyter
Umut GĂĽlac
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.
Polina Schulz
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.
Kurt Rosenberg
Last position:
Lead Solution Architect (AI HealthTech) / interim CTO & Product Co-Owner at Physio-Agil Frankfurt
- General CTO responsibilities (architectural design, operational setup, external runtime product evaluation, investor buy-in, regulatory compliance).
- Software development oversight (implementation on deep-dive-in) plus workflow design.
- Product co-ownership.
- Tech/tools/frameworks: proprietary software (Java, JavaScript), Kubernetes, Postgres, MiniIO, Ollama (internal), several xAI API (external), OpenTofu (Terraform), Keycloak, Kafka, Prometheus, ELK Stack, GitHub, GitHub Workflows, Argo CD, ISO 27001, BSI-ISM, EU AI Act.
Mathew Divine
Last position:
Data Science Expert and AI Strategist at Freelancer
- Built an API to ingest, clean, translate, and index EU tenders documents in Neo4j, enabling hybrid search with RAG and Cypher queries via a Streamlit dashboard
- Deployed the API on AWS Lightsail container services with CI/CD automation via GitHub Actions, ensuring stability through pytest unit and integration tests
- Designed and developed a comprehensive online course on data analysis using ChatGPT for professionals and learners, creating instructional videos and interactive Jupyter notebooks
- Utilized OBS and professional audio equipment to ensure high-quality video and audio content
- Led a CRM data normalization and cleaning project visualized via a Sankey diagram to aid customer understanding and pipeline development
- Implemented and validated a genAI-driven web crawling strategy on AWS, ensuring data quality, scalability, and CRM data augmentation
Olusina Fabunmi
Last position:
Cyber Job Simulation at Deloitte Australia
- Completed a job simulation involving reading web activity logs.
- Supported a client in a cybersecurity breach.
- Answered questions to identify suspicious user activity.
Yevgeniy Ă–sterle
Last position:
Tester, Test & Data Analyst at NORD/LB
- Analyze system requirements and mapping concepts (ETL requirements) for data flows and transformation logic in the bank's DWH
- Analyze data in DB tables and views of the DWH using SQL (DB2)
- Independently define, create, and execute test cases in JIRA Xray (SIT)
- Write SQL queries in DB2 to verify data scenarios and mappings
- Create test plans for SAP FSDP and concurrent projects
- Conduct error and root cause analyses in coordination with business analysts, developers, test managers, and the infrastructure team
- Thoroughly document test results in JIRA Xray
- Coordinate between business analysis, development, DB infrastructure, business units, and external vendors
Michael Weber
Last position:
Business Analyst, Product Owner, Deputy Chairman of the Advisory Board at Federal Ministry, large German city
- We designed a networking platform to improve cooperation and information in the district (Project 71).
- We carried out a tender, defined necessary documents and processes.
- We aimed to ensure that the commissioned service provider carries out quality assurance of the project team's results before implementation.
- We selected a provider.
Rashid Ibragimov
Last position:
Java Developer at IT company
- Data transformations
- IT company with more than 100 employees
- Software production
- Data augmentation and normalization, image transformation, format conversion, merging data from multiple sources
- Toolset: Java, Helm, Kubernetes, Kafka, OpenCV, IntelliJ IDEA, Gradle, Git, Docker, Containers, Scrum
Discover over 15,000 top freelancers
Statistics of experts using Jupyter
Aggregated from the professional profiles of matched freelancers.
Experience
20 years (Germany: 15 years)
Position duration
1.9 years (Germany: 2.9 years)
Positions per freelancer
18 (Germany: 9)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Banking and Finance, Information Technology, Pharmaceutical
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
50% (Germany: 80%)
Doctorate
25% (Germany: 19%)
Certifications per freelancer
6 (Germany: 3)
Most common languages
German, English, Russian
Speak two or more languages
100% (Germany: 99%)
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 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 Jupyter
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
Notebook Work
Jupyter is used for interactive notebooks that mix code, text, charts, and results in one place. Teams use it to explore data, test ideas, document assumptions, and hand work over to other specialists without losing context.
Common Uses
- Data exploration and analysis in Python
- Model prototyping for machine learning work
- Research notes, reports, and repeatable experiments
- Internal demos that need clear, visual steps
Ecosystem
Jupyter work often includes JupyterLab, classic notebooks, IPython, and Python data tools such as pandas, NumPy, and Matplotlib. Strong experts also know how to manage kernels, environments, extensions, and notebook versioning so the work stays stable.
When To Hire
Companies bring in freelance Jupyter specialists when notebooks have grown messy, slow, or hard to share. This is common in analytics teams, product groups, labs, and finance work in Frankfurt where clear documentation and careful review matter.
What Good Experts Do
A strong Jupyter professional writes notebooks that are readable, modular, and easy to rerun. They separate data loading, transformation, and output, avoid hidden state, and know when a notebook should become a script or a package.
Delivery Quality
Good deliverables are not just working cells. Look for clear markdown, consistent outputs, reusable functions, stable environments, and notebooks that another specialist can open and run with little friction.
Frequently asked questions
Key details about Jupyter, drawn from the questions we get asked most.
Jupyter is used for interactive work where code, notes, and charts need to live together. Companies use it for analysis, experimentation, reporting, and quick prototypes that have to be easy to review.
Jupyter is the project name for the notebook ecosystem, while Jupyter Notebook and JupyterLab are the most common interfaces. Many people still say "notebook" when they mean the whole workflow, especially when searching for help.
A project should bring in Jupyter expertise when notebooks are hard to maintain, need to be shared across teams, or must be turned into reliable workflow assets. It also helps when the team needs cleaner structure, better environment handling, or support for review in JupyterLab.
A strong Jupyter freelancer usually also works well with Python, pandas, NumPy, Matplotlib, scikit-learn, and environment tools such as Conda or pip. For more advanced work, they should also understand data cleaning, reproducibility, and basic software structure.
Jupyter is best when exploration, explanation, and iteration matter. Scripts or application code are usually better for production flows, scheduled jobs, and logic that must stay simple to test and maintain.
A simple notebook cleanup may need only a specialist who knows the basics well. Projects with shared research, model validation, or complex data sources need someone who understands structure, reproducibility, and how to avoid notebook drift.
Yes, Jupyter work is often well suited to remote collaboration because notebooks are easy to review and share. In Frankfurt, some teams still want on-site sessions for workshops, stakeholder reviews, or data-sensitive work that needs closer coordination.
Look for notebooks that are clear to read, easy to rerun, and free from hidden shortcuts. A strong Jupyter specialist explains assumptions, uses tidy sections, keeps environments stable, and knows when to move logic out of the notebook.
The average hourly rate of freelancers in Frankfurt, Germany who have used Jupyter in their recent projects is 100 €, which corresponds to a daily rate of about 801 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Jupyter in their recent projects, 100% hold at least a Bachelor's degree, 50% hold at least a Master's degree, and 25% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Jupyter in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Frankfurt, Germany who have used Jupyter in their recent projects are German (100%), English (100%), and Russian (25%).
The most common industries among freelancers in Frankfurt, Germany who have used Jupyter in their recent projects are Banking and Finance (75%), Information Technology (75%), and Pharmaceutical (63%).
The most common business areas among freelancers in Frankfurt, Germany who have used Jupyter in their recent projects are Information Technology (100%), Business Intelligence (88%), and Product Development (75%).
Main locations of FRATCH Experts, who have recently used Jupyter
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 Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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Philipp Thomaschewski
FRATCH CEO
