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Python Expert

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Hire experts who build data pipelines, machine learning systems, web services and automation with Python, supported by tools such as Django, FastAPI, pandas and PyTorch. FRATCH matches you quickly with vetted, available freelancers who fit your technical needs.

Meet FRATCH Experts who have recently used Python

Verified expert

Christel Kristin R.

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SAP Senior / Lead Consultant / Team Lead / Trainer

Schipkau
Christel Kristin R.

Last position:

SAP Senior / Lead Consultant / Team Lead / Trainer at Mercator Leasing GmbH

  • Merging several systems, consulting for SAP Finance / Controlling overall, FI/CO, DRC, F2R, R2R, incoming and outgoing invoice mapping and target postings of contracts and BP from source systems. CAMt53, creation of the technical concept for the migration of various business areas, creation of migration templates and FMD Files, support with data migration, consolidations and data entry, test management for the SAP part, test support, training of end users in all FI and CO areas, FI-AA
Verified expert

André G.

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Consultant for Architecture, Automation and AI in SMEs | Embedded to Strategy | Certified AI Officer

Wiesbaden
André G.

Last position:

Financial Reporting Consultant at Client anonymized (services sector)

Financial reporting as an MVP. Follow-up assignment.

  • Reports on profit and loss, balance sheet and cash flow
  • Budget and personnel metrics (FTE)
  • Implementation as an MVP with a fixed scope
Verified expert

Alwin G.

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IT Director

Essen
Alwin G.

Last position:

IT Interim Manager & AI Strategist

  • Founder of CheironX: AI-supported GRC management (ISO 27001, BSI IT-Grundschutz, TISAX, DORA)
  • Strategic focus on Agentic AI and GenAI for modern IT Governance, Risk & Compliance Management
  • IT interim management and strategic consulting
Verified expert

Michael F.

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Freelancer, Platform Solution Architect

Roth
Michael F.

Last position:

Platform Architect (Project lead) at WĂĽrth IT

I designed and built a self-service AWS platform for Data Science teams with little or no infrastructure-as-code experience. A team writes about 10 lines of Python and gets a deployable stack with full SDLC release cycle that already follows the governance rules. Networking, encryption, IAM and tagging are decided by the platform, not by each team.

New teams or AWS accounts are onboarded with one pull request. Waste prevention and cost control is built into the defaults: Data scientists don't need infrastructure skills.

  • Construct library (AWS CDK, Python). Built a versioned catalog of about 20 hardened constructs for being used in data-science projects with ML context
  • Governance as code
  • Multi-account, multi-tenant
  • Golden-path scaffolding
  • CI/CD and supply chain. Built reusable GitHub Actions workflows
  • Release engineering
  • QA with e2e, contract testing and unit test coverage with each release candidate
Verified expert

Dany-Armand D.

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Senior Data Scientist

Witten
Dany-Armand D.

Last position:

Senior Data Scientist at ibg NDT GmbH

  • Investigate the relationship between Eddy Current Testing (ECT) signals and microstructural properties
  • Detect latent patterns in ECT data that reflect intrinsic material characteristics
  • Develop and validate predictive models for microstructural classification and quantification, using hardness and case depth as benchmarks
  • Apply Bayesian Structural Equation Modeling for advanced data analysis
Verified expert

Lutz E.

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Software Engineer Full-Stack (React/Next.js, TypeScript, C#/.NET, Python, Node.js)

Solingen
Lutz E.

Last position:

Freelance Software Developer – GoPro MultiCam Control via COHN at Plutos Company UG

  • Developed a pilot system to control and monitor multiple GoPro cameras
  • Implemented start, stop, status, media, download and diagnostic functions via COHN endpoints
  • Built camera detection, individual and group control, and stable session/KeepAlive logic
  • Set up a download pipeline with a queue, retry handling and temporary files
  • Ensured consistent session, folder and file naming for multicamera recordings
  • Integrated provisioning, certificates and network operations
Verified expert

Michael S.

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IT & Test Consultant

Mainz
Michael S.

Last position:

IT & Test Consultant at Testing Experts GmbH

AI Readiness - Part 3: Creating an e-book on the use of AI in software testing

  • Designed and created an e-book on the sensible and safe use of AI in software testing from the perspective of an experienced test expert.
  • Used generative AI (ChatGPT, Perplexity Pro) as a sparring partner for structuring, wording suggestions and creating variations, with all content finally reviewed and approved using my own expertise.
  • Developed practical insights into the opportunities and risks of AI in testing, with a special focus on collaboration between testers and AI instead of “tester vs. AI”.
  • Title: “11 starke GrĂĽnde: Dream-Team statt Rivalen - Tester und KI sind gemeinsam unschlagbar”
  • Subtitle: “Wie Mensch und Maschine im Softwaretest das perfekte Team bilden – und warum reines KI-Testing riskant ist.”
  • Planned use of the e-book as a basis for workshops, customer meetings or internal training.
  • Technology: Generative AI, ChatGPT, Perplexity Pro, Microsoft Word, Adobe Acrobat, many years of hands-on professional testing experience, common sense.
Verified expert

Franz B.

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Program Lead • Portfolio Manager • Digitalization & Transformation

Munich
Franz B.

Last position:

Product Development (AI) at Self-initiated

AI phone assistant platform

Claude Code, Google AI Studio, Python, LLM / Voice-AI, PostgreSQL

  • Designed and hands-on developed an AI-powered phone assistant platform (Voice-AI / LLM)—from idea and architecture through to MVP/product.
  • Built agentic workflows and end-to-end automations with Claude Code and Google AI Studio.
  • Also supported AI-powered delivery in client engagements: using Claude Code for governance documentation, requirements drafts, and automations.
Verified expert

Robert D.

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Software Architect

LĂĽbeck
Robert D.

Last position:

Java Software Architect at adesso insurance solutions GmbH

Verified expert

Paul W.

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Enterprise & Solution Architect · Senior IT Program Manager Freelance IT Consultant — SAP · Salesforce · Cloud · AI/Agentic

MĂĽnchen
Paul W.

Last position:

Enterprise Architect at ePrimo GmbH

Led the end-to-end integration and migration architecture for decommissioning SAP IS-U market communication and transitioning to Salesforce Marketing Cloud (SFMC) with E.ON IT Services — covering regulated EDIFACT market messaging, a three-phase data migration (transfer of market message inventory after cutover), redesign of market communication processes, and full GDPR and German energy-market compliance.

  • Designed the three-tier target architecture (SAP IS-U → NScale B2B gateway → SFMC) processing 50,000–100,000 EDIFACT messages daily within sub-5-minute SLAs.
  • Architected the three-phase data migration: 36 months of historical data, zero-loss cutover of in-flight market messages, and near-real-time CDC synchronization.
  • Delivered secure, BDEW/GDPR-compliant integration (AS2/OFTP2, RFC/IDoc, REST APIs, OAuth 2.0, Azure AD, AWS S3) achieving >99.5% uptime, <0.1% migration discrepancy, and RTO <4 hours.
  • Applied BPMN to model and optimize the market communication processes.

Technologies: SAP IS-U, NScale, Salesforce Marketing Cloud, EDIFACT, OAuth 2.0, Azure AD, AWS S3, BPMN, Jira, Confluence, Draw.io

Verified expert

Fadi S.

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Operational AI & Data Engineering Consultant

Oberhausen
Fadi S.

Last position:

Data Scientist at E-Commerce

  • Designed and developed a production-ready data platform based on Microsoft Fabric for an e-commerce company
  • Built a scalable Medallion Architecture (Bronze, Silver, Gold) with Lakehouse and Delta Lake as the foundation for analytics and AI applications
  • Developed a metadata-driven ETL platform with PySpark and a generic Incremental Loading Framework (SQL Server → Bronze → Silver → Gold)
  • Developed reusable components for Microsoft Fabric Notebooks to standardize data integration, transformation, and validation
  • Implemented automated data pipelines including monitoring, logging, error handling, and Delta MERGE strategies for stable production operations
  • Built a business layer architecture for reporting, data warehousing, and reusable data products
  • Integrated heterogeneous data sources via SQL Server, REST APIs, Amazon SP API, and Google Analytics 4
  • Worked closely with business departments to analyze business requirements and translate them into scalable data architectures

Technologies: Microsoft Fabric, PySpark, Python, SQL Server, Delta Lake, Lakehouse, OneLake, Data Factory, Data Warehouse, REST APIs, Amazon SP-API, Google Analytics 4

Verified expert

Vaios K.

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Senior Product Manager | AI, Platform & API Products

Berlin
Vaios K.

Last position:

Product Manager & Strategic Advisor at Freelance, Lovable, Dreamarium

  • Advise early-stage startups on product vision, roadmapping, and GTM strategy, combining PMP and Stanford PM training with hands-on technical execution.
  • Lovable: built and led a 200+ member community program for AI-native founders, bridging real-time founder feedback into product roadmap decisions.
  • Lead customer discovery and OKR design engagements, scoping AI integration opportunities across client products.
Verified expert

Vladimir E.

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Technical Executive, Principal Architect

Aurachtal
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.
Verified expert

Niko S.

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Developing Architect / Solution Architect

Hamburg
Niko S.

Last position:

Developing Architect, Technical Lead "gridlytics" at HH Energienetze

  • Built a data integration platform for high-, medium- and low-voltage assets to enable contextual analysis of time series with master data from SCADA control systems (IEC 60870 104), INIS and SAP.
  • Responsible for the architecture and implementation of the solution, and acted as a sparring partner for the Product Owner.
  • Technologies used: Kotlin, Spring Boot, Maven, TimescaleDB, PostgreSQL, liquibase, Elements IoT, Docker, Kubernetes, Grafana, Python, jupyter and various API gateways.

Discover over 15,000 top freelancers

Statistics of experts using Python

Aggregated from the professional profiles of matched freelancers.

Experience

16 years

Python experts have 16 years of professional experience on average.

Position duration

5.1 years

Python experts stay in a single position for 5.1 years on average.

Positions per freelancer

10

Python experts have completed 10 positions on average over the course of their careers.

Top business areas

Information Technology, Product Development, Project Management

Python experts have gathered most of their hands-on project experience in Information Technology, Product Development, and Project Management.

Top industries

Information Technology, Manufacturing, Automotive

Python experts are most in demand in Information Technology, Manufacturing, and Automotive.

Certification focus areas

Information Technology, Project Management, Product Development

Python experts earn their certifications most often in Information Technology, Project Management, and Product Development.

Bachelor's degree or higher

94%

94% of Python experts hold at least a Bachelor's degree.

Master's degree or higher

69%

69% of Python experts hold at least a Master's degree.

Doctorate

12%

12% of Python experts have a doctorate (PhD).

Certifications per freelancer

3

Python experts hold 3 professional certifications on average.

Most common languages

English, German, French

Python experts most often speak English, German, and French.

Speak two or more languages

98%

98% of Python experts speak two or more languages.

Based on our profile pool as of 5 Nov 2026.

Daily rate distribution

0% 25% 50% 75% 100%
10% of Python experts charge less than €400 per day.
45% of Python experts charge between €400 and €800 per day.
38% of Python experts charge between €800 and €1200 per day.
4% of Python experts charge between €1200 and €1600 per day.
2% of Python experts charge €1600 or more per day.
<€400 €400-​800 €800-​1200 €1200-​1600 €1600+

The chart shows how the daily rates of experts in this technology are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.

Average rates of experts using Python

Rates are based on recent contracts and do not include FRATCH margin.

800
600
400
200
Rate comparison chart
Daily rate avg. 723 €

The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.

800
600
400
200
Rate comparison chart
Median rate 760 €

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 5 Nov 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.

Python 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 (81%)
  • Manufacturing (39%)
  • Automotive (38%)
  • Banking and Finance (37%)
  • Education (35%)
  • Professional Services (31%)
  • Healthcare (28%)
  • Retail (27%)

Please note that freelancers can work across multiple industries, so percentages overlap.

About the technology

Python’s role

Python is a general-purpose programming language used for web services, data processing, machine learning, automation and scientific software. Its readable syntax and broad standard library make it suitable for prototypes, internal tools and production systems. CPython is the reference implementation most teams use.

What it builds

Python supports products and workflows across many technical environments:

  • APIs and web applications with Django, Flask or FastAPI
  • Data pipelines, analysis tools and reporting systems
  • Machine learning and artificial intelligence services
  • Test automation, scripts and internal productivity tools
  • Scientific, financial and research software

Ecosystem and tooling

Strong Python work depends on more than language syntax. Professionals use pandas and NumPy for data, PyTorch or scikit-learn for modeling, and Celery for background processing. They also work with PostgreSQL, Redis, Docker, Git, CI pipelines and cloud services, while managing environments with uv, Poetry or virtualenv.

When expertise matters

Companies bring in freelance Python expertise when a data workflow is unreliable, an API needs to scale, or a prototype must become maintainable production software. Specialists can also modernize legacy scripts, connect third-party services, improve test coverage and establish deployment practices. Clear scope, ownership of existing code and access to relevant systems help remote collaboration run smoothly.

What strong specialists deliver

A capable Python professional chooses simple structures before adding complexity. They define interfaces, isolate dependencies and write tests that protect important behavior. They understand performance, security, observability and error handling, then document decisions so other teams can operate the result. Experience with the relevant framework and deployment environment matters as much as language fluency.

Selecting the right fit

Review a specialist’s experience with the exact kind of system you need, not just a list of Python libraries. Ask how they test data quality, handle secrets, monitor services and manage changes in shared repositories. A practical assessment should examine a small, relevant task and the reasoning behind it. Communication style, written clarity and comfort with your team’s working language are equally important.

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Frequently asked questions

The facts hiring teams ask for most often when it comes to Python.

Python is used for web APIs, data analysis, machine learning, automation, scientific computing and internal business tools. Its ecosystem lets teams use one language across experimentation, integration and production services.

Python usually offers faster development and a strong data and machine learning ecosystem. JavaScript is central to browser applications, Java is common in large enterprise systems, and Go is often selected for compact, high-concurrency services. The right choice depends on runtime needs, team skills and available libraries.

Python work often connects with SQL, REST and GraphQL APIs, Docker, Git, Linux, cloud services and CI pipelines. Depending on the project, useful adjacent skills include Django or FastAPI, pandas, NumPy, PyTorch, Kubernetes and message queues.

Python project needs vary with risk and scope rather than a fixed tenure. A small automation task may need focused scripting and testing skills, while a regulated data product or distributed API requires architecture, security, observability and deployment experience.

Python specialists can work remotely when the team provides repository access, clear interfaces, test data and dependable communication routines. Shared documentation, code review and predictable release practices matter more than physical proximity for many projects.

Python web projects often use Django when they need an integrated framework with authentication, administration and database support. Flask suits smaller, modular services, while FastAPI is a strong option for typed APIs and asynchronous workloads. The decision should follow the product’s boundaries and operational needs.

Python quality shows in readable structure, meaningful tests, safe dependency management and clear error handling. Ask a specialist to explain trade-offs, demonstrate how they would monitor the system and review a relevant code sample for maintainability rather than cleverness.

Python professionals are expected to work beyond isolated scripts. Production assignments commonly involve version control, packaging, testing, databases, APIs, deployment and collaboration with product or data teams. Familiarity with the project’s domain and the ability to explain technical decisions are valuable.

The average hourly rate of freelancers who have used Python in their recent projects is 90 €, which corresponds to a daily rate of about 723 € based on an 8-hour working day.

Of the freelancers who have used Python in their recent projects, 94% hold at least a Bachelor's degree, 69% hold at least a Master's degree, and 12% hold a doctorate.

On average, freelancers who have used Python in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 5.1 years.

The most common languages among freelancers who have used Python in their recent projects are English (98%), German (97%), and French (18%).

The most common industries among freelancers who have used Python in their recent projects are Information Technology (81%), Manufacturing (39%), and Automotive (38%).

The most common business areas among freelancers who have used Python in their recent projects are Information Technology (90%), Product Development (79%), and Project Management (51%).

Main locations of FRATCH Experts, who have recently used Python

Our freelancers and interim experts are at home all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.

In Austria our freelancers and interim experts support companies from Vienna to Graz — on-site where your project needs them, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.

Across Switzerland our specialists are active in Zurich, Geneva, Basel and Bern — working on-site or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.

Zurich Geneva Basel Bern

Countries:

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