Celery Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Celery
Sanju Raj Prasad
Last position:
Software Developer at Senior Connect GmbH
- Created complex backend systems (Fastapi Python, GCP cloud functions, APIs, integration tests) using Typescript.
- Worked with firebase and firestore databases, implementing transactional operations, scheduling jobs, and migrations.
- Implemented GCP dashboards for thorough monitoring and custom alerts in case of anomaly traffic.
- Implemented Sentry for better debugging, error tracking and overall monitoring of the Next.js frontend.
- Implemented story tests for UI related testing.
- Implemented Typesense in Python Fastapi backend, for improved text based searching along with typo handlings.
Nemanja Milenković
Last position:
AI Engineer / Senior Backend Engineer at Intelycx
Manufacturing intelligence platform with enterprise workflows, RAG, real-time AI assistant features, and multi-repository backend architecture.
- Built and extended production AI/backend services with Django, DRF, FastAPI, GraphQL, Celery, PostgreSQL, MySQL, Redis, and WebSockets across a modular multi-repository platform.
- Contributed to ARIS V2, a real-time manufacturing AI assistant using LangChain, LangGraph, MCP tool orchestration, planning/execution flows, OpenAI, AWS Bedrock, Qdrant, and Elasticsearch/OpenSearch-backed retrieval.
- Supported rollout expansion from ARIS V1 in 4 of 17 client production plants to ARIS V2 currently active in 13 of 17 plants, increasing real-world deployment coverage to more than 50% of the client footprint.
- Worked on document-grounded RAG functionality including ingestion, OCR, chunking, embeddings, indexing, retrieval, reranking, and grounded answer generation for industrial workflows.
Stack: Python, Django, DRF, FastAPI, LangChain, LangGraph, GraphQL, Celery, WebSockets, OpenAI, AWS Bedrock, Qdrant, Elasticsearch/OpenSearch, PostgreSQL, MySQL, Redis, Docker.
Mukund Biradar
Last position:
Voice AI Chatbot - Real-Time Audio Assistant
- ▶ Built real-time voice assistant (STT → LLM → TTS pipeline) benchmarking and evaluating multiple STT providers including faster-whisper and Azure Speech. achieved sub-3s latency, Groq API (Llama 3) with multi-turn memory - directly handling edge cases in dictation, names and passcode recognition.
Ashutosh Tripathi
Last position:
Consultant at Brillio Technologies
- Developed backend for Audit Management Tool using Node.js/Express with Workday API integration.
- Built secure file handling (PDF, PPT, CSV) with AWS S3 and database support via PostgreSQL, Prisma, and MongoDB.
- Implemented validation, role-based access, and audit trails for compliance and data integrity.
Muzamal Ali
Last position:
Data Scientist / AI Consultant at HelmX
- Delivered AI and data science solutions, including LLM-based chatbots and data pipelines, improving operational efficiency.
- Collaborated on product features, achieving measurable impact and maintaining strong client relationships.
Niko Karajannis
Last position:
Co-founder & AI Engineer at KAIKI GmbH
End-to-end responsibility for all products - concept, architecture, development, and production operation as the sole developer; in addition, customer meetings, proposals, and marketing.
Underwriting Copilot - AI assistant for industrial insurance (in production at customer sites)
- Supports underwriters in analyzing industrial insurance submissions - in production use at an industrial insurer.
- Framework-independent RAG architecture with Hybrid Search (BM25 + pgvector) across large, mixed document sets.
- Two-stage evaluation and observability pipeline (code assertions + LLM-as-Judge) that makes answer quality, retrieval accuracy, and citation integrity measurable in a regression-safe way.
Kaiki Menu Analyzer - Data intelligence platform (in production at customer sites)
- Automatically captures and analyzes menu data from around 25,000 German restaurants.
- Scalable 7-container architecture (FastAPI, partitioned PostgreSQL, Redis/RQ) with LLM-supported extraction of structured data from PDF, HTML, and images.
- Full CI/CD pipelines (GitHub Actions), production cloud deployment, interactive dashboards (Dash).
Kaiki GEO Atlas - GEO platform (in production at customer sites)
- Measures brand visibility across five AI engines (ChatGPT, Gemini, Perplexity, Grok, Claude), each augmented with web search, orchestrated as a DAG workflow pipeline (Dispatcher → Sub-workflows → Scoring → Report) with fail isolation.
- 6-container deployment (FastAPI, Celery, Redis, PostgreSQL); LLM cost estimation, PDF audit report, rule-based cross-signal insights (no extra LLM cost).
Data Pipeline & Analytics Platform - competitive analysis in the automotive aftermarket
- Automated data pipeline with gap analysis algorithms and role-based access control; 230+ tests.
- Backend with FastAPI, PostgreSQL, SQLAlchemy.
Product development (actively in progress)
BankingGPT - AI assistant for complaint management in cooperative banking
- Security architecture at the core: no AI draft reaches the customer without human approval - the approval decision is in auditable code, not in the language model (monotonic: the model may escalate, never downgrade).
- Real agentic building blocks, each with its own boundary: the model chooses tools itself through an MCP server (read-only, allowlist, capped, fail-safe); sensitive cases are handed off via an open A2A protocol (JSON-RPC, Agent Card, message/send/tasks/get; client implemented by me) to a separate specialist agent (securities/law), which never lowers the review requirement (pinned by test).
- Evaluation-driven over ten analysis rounds; uncovered a security flaw through independent review and blind tests that nine automated runs had missed.
- Voice AI frontend, responding live: covered cases are answered in the conversation, sensitive ones escalate before generation; response latency < 7 s measured (local GPU STT/TTS).
Stack & production readiness: Python, pydantic-ai, FastAPI/Celery, PostgreSQL/pgvector, FastMCP, fasta2a, Docker; multi-tenant capable (physical vector isolation per tenant), PII encrypted, OWASP-LLM reviewed, 275 tests, CI/CD; vendor-portable (Ollama / EU Cloud Vertex).
After-Sales Assistant - agentic RAG/GraphRAG assistant on public OEM manuals (automotive after-sales)
- Genuinely agentic on LangGraph: ReAct agent with four tools and conversation memory - the model decides on its own whether to use the manual (RAG, Chroma), a knowledge graph (GraphRAG, Neo4j/Cypher - decodes warning lights), or a workshop/booking service.
- Human-in-the-Loop before the irreversible action: before every appointment booking, the graph pauses (interrupt) and gets the driver's explicit confirmation - the same approval-before-action discipline as in BankingGPT, in a different framework.
- Eval as CI gate: a three-part scorecard (RAGAS grounding + deterministic tool-routing accuracy + DeepEval safety: does the answer mention the warning first when there is a critical warning?) blocks the pipeline; provider-agnostic (OpenAI/Azure/Anthropic), FastAPI with token streaming.
Stack: Python, LangChain/LangGraph, Chroma, Neo4j, RAGAS/DeepEval, FastAPI, Docker.
Kevin Meinon
Last position:
Backend & Infrastructure Engineer at Mileo Systems GmbH
- Engineered production-ready Azure environments using Terraform, ensuring consistent infrastructure parity across VNets and Resource Groups
- Implemented Microsoft Fabric tenant and workspace architecture for multi-stage Medallion data processing pipelines
- Designed secure data pathways using Managed Private Endpoints for isolated Azure Storage access
- Managed Service Principals and authentication tokens for secure REST API integrations
Yevhen Chubchyk
Last position:
Python/Django Developer at Deuta Werke
- Expansion and maintenance of existing custom information systems based on Django
- Technologies used: Django, Django REST Framework, MySQL, Docker
Nikolai Rybalkin
Last position:
Principal Engineer (Contract) at Independent Contractor
- Built multi-tenant warehouse management SaaS: 40 API modules, 150+ routes, real-time updates via SignalR
- Technologies: React, TypeScript, Redux Toolkit, RTK Query, Webpack, .NET 8, PostgreSQL, SignalR, Docker, GitHub Actions
- Landing: Next.js 14, Tailwind CSS, 17 localizations, Stripe payments (SEPA + cards)
- Testing: xUnit (150+ files), Jest, Playwright E2E; CI/CD: Docker, GitHub Actions
- Telegram AI agent: daily inventory reports, shipment alerts and warehouse monitoring delivered to mobile
- Background jobs and scheduled tasks for automated reporting, alerts, and data synchronization
- Built German e-invoicing SaaS (XRechnung, ZUGFeRD), GDPR compliant, multi-tenant architecture
- Technologies: React, TypeScript, RTK Query, Python, FastAPI, PostgreSQL, Redis, Celery; Testing: pytest (294 tests), Playwright
- Implemented async task queues (Celery + Redis) and scheduled jobs for invoice processing, email notifications, and DATEV export
- Developed AI-powered content automation platform: analyzes Git commits, generates and publishes posts to LinkedIn and Discord, responds to GitHub Issues automatically
- Cron-based automated publishing pipeline and scheduled content generation and distribution across platforms
- Multi-LLM architecture (OpenAI, Claude, Gemini) with pluggable provider system and RAG-based knowledge assistant integrated across all SaaS products
Murad Ali
Last position:
AI Agents Automation - LLM-Powered Agentic System
- Developed a multi-agent system connecting LangChain ZeroShotAgent with custom tools for live APIs and task automation.
- Built a FastAPI backend for Jira ticket creation, triage and assignment, auto classification of severity, deduplication, SLA setup, on-call rotation, bidirectional sync of status and comments.
- Added Slack alerts and RAG knowledge lookup with FAISS or pgvector to suggest fixes, optional PagerDuty escalation on policy breaches.
- Orchestrated agents with a router and a Celery plus Redis queue, retries with backoff, rate limits, idempotency keys, human in the loop approvals.
- Implemented guardrails and observability, prompt versioning, token and cost budgets, PII redaction, tool-use allowlists, timeouts, OpenTelemetry tracing, dashboards for accuracy and latency, deployed on Kubernetes with feature flags and canary rollouts.
Christoph Neumann
Last position:
Technical Advisor at Leximate
- Set up AI-first Legal-Tech platform using latest LLM models and agentic development workflows.
- Launched MVP in under 5 days from idea to code.
- Setup AI-first development workflows "from call to shipped feature".
Frank Bohnsack
Last position:
Software Engineer at Freelancer
- Freelance software engineer focusing on backend (Python/Django) and frontend (VueJS).
Patrick Seelemeyer
Last position:
Senior Software Engineer at Delivery Hero
- Led a team of 6 software engineers to develop and maintain an AI-driven healthcare platform, enabling automated diagnostics and prescriptions based on real-time ECG data analysis
- Designed and developed a robust Revenue Cycle Management (RCM) system, integrating HL7 and FHIR APIs to enable seamless interoperability, real-time data exchange, and HIPAA-compliant data handling, improving billing efficiency, claim processing, and regulatory adherence in healthcare operations
- Migrated a legacy monolithic application to a scalable microservices architecture, enhancing system modularity, scalability and maintainability while implementing key design patterns such as Strangler, Database-per-Service, API Gateway, Saga and CQRS for efficient service communication and transaction management
- Architected and led a C# 9/.NET 6 microservices ecosystem handling hotel reservations, payments, and loyalty programs, enabling 99.99% uptime across 10+ services
- Defined OpenAPI/Swagger contracts and auto-generated client SDKs, reducing front-to-backend integration time by 50%
- Containerized each service with Docker and orchestrated deployments via Kubernetes, slashing release lead time from days to hours
- Designed PostgreSQL schemas optimized for high-volume transactional workloads and implemented Redis caching layers to accelerate read-heavy endpoints by 80%
- Built Kafka streaming pipelines for real-time availability updates and audit logs, processing 2 million+ events per hour with end-to-end delivery guarantees
- Implemented unit and integration tests for React applications using Jest and React Testing Library, ensuring 80%+ test coverage, improving component reliability, and preventing regressions
- Defined and deployed AWS cloud infrastructure using Terraform, while containerizing and orchestrating microservices with Docker and Kubernetes, improving automation and system scalability
- Built a scalable full-stack booking application using React 18 and Django REST Framework, integrating Celery and Redis for asynchronous task processing, while deploying on GCP with Cloud Run and Firestore, enabling real-time scheduling, payment processing, and automated notifications
- Mentored junior developers through code reviews, pair programming, and knowledge-sharing sessions, improving team efficiency by 30% while maintaining comprehensive API documentation using Swagger/OpenAPI
Şüheda Yıldırım
Last position:
LLM Backend Engineer at Alpha AI
- Built a production-grade LLM pipeline to automate multi-step insurance data cleaning and schema alignment.
- Designed and built a full-scale FastAPI + Celery distributed processing system.
- Created a 12-step AI pipeline for enterprise insurance data standardization.
- Integrated Azure AI Foundry for deterministic LLM-based data cleaning.
- Developed enterprise-level SharePoint integration.
- Optimized performance, monitoring, and developer experience.
- Implemented Infrastructure-as-Code with Terraform.
Christoph Beberweil
Last position:
Freelancer & Managing Director at Capsimity GmbH
Discover over 15,000 top freelancers
Statistics of experts using Celery
Aggregated from the professional profiles of matched freelancers.
Experience
13 years
Position duration
2.2 years
Positions per freelancer
6
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Education, Healthcare
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
100%
Master's degree or higher
62%
Certifications per freelancer
1
Most common languages
English, German, Hindi
Speak two or more languages
93%
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 Germany 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 Germany using Celery
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 Celery does
Celery is a Python task queue for background work that should not block a web app or API. Teams use it for email sending, report generation, image processing, imports, and other asynchronous jobs. It fits systems that need retries, scheduled runs, and clear worker control.
Core building blocks
- Celery app setup and task routing
- Workers, queues, and brokers such as Redis or RabbitMQ
- Result handling, retries, and time limits
- Periodic jobs with celery beat
- Monitoring and debugging with Flower or logs
Where it fits
Strong Celery specialists understand how tasks move through Django, FastAPI, or Flask back ends. They know when to split work into small jobs, how to avoid duplicate processing, and how to keep long-running work away from the request path. In Germany, this often matters for SaaS, logistics, finance, and internal business tools.
When to bring in help
Bring in freelance expertise when task queues stall, jobs fail silently, or worker throughput drops. You also need help when a team is adding scheduling, chaining tasks, or moving from simple scripts to reliable production processing. Another common case is a review of broker choice, queue layout, and failure handling.
What strong specialists do
A strong Celery professional writes tasks that are idempotent, easy to retry, and safe under load. They separate short and long jobs, design sensible queue priorities, and keep observability in place. They also document runbooks so the team can operate the system without guesswork.
Ecosystem skills
Celery work rarely stands alone. Useful adjacent skills include Python, Django, Redis, RabbitMQ, Docker, and cloud deployment. Good specialists also understand logging, metrics, and how scheduled work interacts with web requests, databases, and external APIs.
Frequently asked questions
Curious about Celery? Here are the answers that come up again and again.
Celery is used for work that should run outside the main web request, such as sending emails, processing files, generating reports, and calling slow external services. It helps keep apps responsive while background jobs run in workers. It is also a common choice for scheduled tasks through celery beat.
Celery is stronger than a simple queue when you need retries, routing, acknowledgements, and worker management. Compared with cron, it handles event-driven jobs and distributed processing much better. Cron still fits a few fixed schedules, but Celery is better for app-driven background work.
A Celery project often includes Redis or RabbitMQ as the broker, plus Flower or logs for monitoring. In web stacks, it is commonly paired with Django, FastAPI, or Flask. Container tools like Docker are also useful when the workers need to run in the same environment as the app.
Ask how the Celery specialist handles retries, failed jobs, queue design, and task idempotency. You should also ask which broker they recommend and how they monitor workers in production. Clear answers here show whether they can keep background processing stable.
A Celery task queue can be set up quickly, but production work needs more than basic task writing. You want someone who has handled broker configuration, worker scaling, and failure recovery. If your system has many moving parts, choose a specialist who has shipped similar background-processing flows before.
Yes, Celery work is usually easy to do remotely because most of the work is code, queue design, and system review. For teams in Germany, it helps if the specialist can work in English and join short planning calls in the local time zone. On-site time is rarely required unless access or security rules demand it.
A Celery specialist understands worker behavior, broker limits, retry storms, and how tasks fail under load. They do more than write background code; they shape reliable execution. That includes observability, queue separation, and safe task design.
Celery is often the better choice when you need a mature ecosystem, flexible routing, and broad production experience in Python teams. RQ can be simpler, and Dramatiq can feel leaner, but both may suit smaller needs. The right choice depends on your workload, failure model, and operational setup.
The average hourly rate of freelancers in Germany who have used Celery in their recent projects is 75 €, which corresponds to a daily rate of about 600 € based on an 8-hour working day.
Of the freelancers in Germany who have used Celery in their recent projects, 100% hold at least a Bachelor's degree and 62% hold at least a Master's degree.
On average, freelancers in Germany who have used Celery in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Germany who have used Celery in their recent projects are English (93%), German (87%), and Hindi (13%).
The most common industries among freelancers in Germany who have used Celery in their recent projects are Information Technology (100%), Education (40%), and Healthcare (40%).
The most common business areas among freelancers in Germany who have used Celery in their recent projects are Information Technology (100%), Product Development (93%), and Business Intelligence (47%).
Main locations of FRATCH Experts, who have recently used Celery
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 Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
