Redis Expert in Berlin
for fast, reliable data systems with precise AI matchingHire experts who design caching layers, real-time features and resilient data services with Redis, Redis Cluster and Streams. FRATCH matches you quickly with vetted, available freelancers who fit your technical needs.
Meet FRATCH Experts in Berlin, who have recently used Redis
Alois R.
Last position:
Senior Fullstack Developer at brandung GmbH
- Opt-in RAG extension over tenant-owned data sources (SharePoint, Confluence) on existing multi-tenant enterprise AI platform
- Architecture: ADRs, solution evaluations, permission strategy, cost modeling
- End-to-end SharePoint and Confluence connectors: OAuth consent flows, token refresh, metadata sync, search integration
- Permission resolution: ACL indexing at ingestion and query-time verification (document-level security)
- Elasticsearch hybrid search (semantic + keyword) with RRF scoring
- RAG chat with context injection and source citations
- Stack: Elastic Cloud, Elasticsearch, Docker, Northflank, Next.js, React, TypeScript, Prisma, Microsoft Graph API, Atlassian REST API, OAuth 2.0
Imran A.
Last position:
Software Engineer II at LivePerson Germany GmbH
- Led development of 15+ microservices (Java 17, Spring Boot) driving customer interactions; migrated from on-prem to GCP Kubernetes, improving scalability and reducing infra cost by 20%.
- Optimized user services with CouchDB caching and API refactoring, cutting response times by 35% and enhancing customer experience.
- Implemented canary deployments, FluxCD GitOps, and CI/CD optimizations in GitLab, reducing release lead time by 25% and enabling zero-downtime rollouts.
- Set up Grafana health checks and Anodot alerts for latency, error, and throughput monitoring, reducing MTTR by 40%.
- Built secure APIs using OAuth2, DPoP, and Gatekeeper, integrated REST and GraphQL, and achieved 90%+ test coverage with unit and E2E tests.
- Mentored junior developers, promoted Agile best practices, and collaborated cross-functionally to deliver high-impact, reliable customer-facing features.
Viktor S.
Last position:
AI Engineer (Freelance) at Empion
Enterprise AI content categorization and AI-powered web research.
- Built multi-LLM evaluation framework with annotated data
- Iterated LLM error rates based on annotated datasets
- Implemented AI-powered web research pipeline Stack: LLM, evals, OpenRouter, Python, Node.js, TypeScript, React
Tommy S.
Last position:
Process Manager · Order-to-Cash & Automation at EWE Tel GmbH
- Root cause analysis of complex business, technical, and data-related errors in PowerCloud across process, booking, and system boundaries.
- Data-driven management of payments and receivables; contributed to reducing historical receivables from over 100 Mio. EUR to under 25 Mio. EUR.
- Identification of automation and straight-through processing potential at the interface between business departments, IT, and external service providers.
Julius H.
Last position:
Freelancer at Freelancer — Pharma Industry
- Led migration to GCP using Terraform, GKE, and GitOps, improving deployment consistency and scalability
- Implemented Datadog observability stack via Terraform and datadog-operator
- Established automated end-to-end tests and on-call processes, improving incident response and service reliability
- Migrated from NGINX Ingress Controller to Kubernetes Gateway API (NGINX Gateway Fabric)
- Migrated stateful services (PostgreSQL and Redis) to GCP, improving scalability and operational reliability
Jorge N.
Last position:
Senior Developer at NDA
AI Platform Backend – Senior Developer
Hired to design and build an AI platform backend from the ground up, including multi-provider LLM orchestration and real-time infrastructure for AI influencer personas at scale.
Tasks and Responsibilities
- Architected and implemented a multi-LLM orchestration layer with Semantic Kernel to integrate GPT-4 and other providers for core platform logic and AI influencer personas, reducing model-switching overhead by abstracting provider APIs behind a unified interface.
- Designed and developed a backend from the ground up in C# / .NET 10, including domain modeling with DDD, a versioned RESTful API layer, and cloud infrastructure on Azure.
- Built real-time chat infrastructure with Server-Sent Events (SSE), message persistence, and delivery guarantees for running AI influencer personas live at scale.
- Developed a media management service with cloud object storage integration for uploading and retrieving influencer-generated content.
- Created an integration and unit test suite with data seeding for reliable regression testing across all core platform flows, significantly reducing the production error rate.
Tools and Technologies: C#, .NET, ASP.NET Core, Python, TypeScript, MySQL, Semantic Kernel, EF Core, Minimal APIs, LLM Orchestration, Prompt Engineering, Agentic AI, Generative AI, AI-Assisted Engineering, Claude Code, GitHub Copilot, Google Gemini, OpenAI API, Ollama, Redis, Azure, Azure Container Apps, Azure Database for MySQL, Docker, GitHub Actions, Clean Architecture, Vertical Slice Architecture, CQRS, Domain-Driven Design, REST API, xUnit, Integration Testing, Unit Testing, Jira, Confluence, Scrum
Caleb C.
Last position:
Senior Python Backend Engineer at Simon-Kucher
Transmission system operator – network provisioning platform (team lead)
- Designed the saga orchestrator in Python that provisions network fabrics with rollback.
- Split IP, identity, and resource allocation into bounded contexts with their own databases and typed clients.
- Implemented data access using DDD repositories and units of work, with no SQL in the domain code.
- Required integration tests using real PostgreSQL and RabbitMQ containers, and API fuzzing for every service.
- Introduced an agent workflow where a spec starts each change and a human approves every merge.
- Rolled out OpenTelemetry auto-instrumentation through GitOps across eighteen Kubernetes clusters.
- Led incident response for stuck provisioning and recorded every outage as a post-mortem.
Languages and software used: Python, FastAPI, Pydantic v2, SQLAlchemy async, PostgreSQL, RabbitMQ, Celery, pytest, testcontainers, schemathesis, Helm, Flux CD, GitLab CI, OpenTelemetry, pi coding agent.
Software product company – datacenter simulation SaaS (backend development)
- Built the asynchronous simulation pipeline as the second-largest contributor among more than twenty team members.
- Tagged every image by commit SHA and semver in the GitHub Actions deployment workflows.
- Diagnosed the RabbitMQ memory alarm that froze every simulation and fixed the limits in the Helm chart.
- Converted the test suite to function-style pytest, with coverage reported in every pipeline.
Languages and software used: Python, FastAPI, SQLAlchemy, Alembic, Celery, RabbitMQ, Redis, PostgreSQL, S3, EKS, Helm, Keycloak, GitHub Actions, pytest, mypy, ruff, SonarQube.
Internal AI platform – model serving and telemetry
- Built the FastAPI service that deploys open-weight models on GPU tiers as OpenAI-compatible endpoints.
- Upgraded production EKS by two Kubernetes minor versions and fixed zone-bound storage faults.
- Traced every model call, including its token count, cost, and latency, through the OpenTelemetry operator.
Languages and software used: Python, FastAPI, vLLM, LangGraph, pydantic-ai, OpenAI and Anthropic APIs, EKS, Helm, Flux CD, Terraform, GitLab CI, OpenTelemetry, Grafana.
Mukund B.
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.
Nada S.
Last position:
Freelance Senior Frontend Engineer at Self-Employed
- Senior software engineer focused on React, TypeScript and AI-assisted product workflows
- Build frontend systems for complex SaaS products, internal tools and operational workflows
- Recent work includes AI evaluation tooling, support reliability analysis and developer-focused QA systems
- Available for freelance and contract engagements, especially remote-first projects
Rüdiger S.
Last position:
Full-Stack Software Engineer / Consultant for Digitalization at ARTEVENT
Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.
Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.
Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.
Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.
Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.
Hamza K.
Last position:
Academic Research Contributor in Health Sector (Volunteer) at n/a
- Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
- Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.
Murad H.
Last position:
Founder & Technical Lead at Hubpoint.Ai
- Founded an AI-powered scheduling and business-management SaaS for SMBs, owning technology strategy, architecture, product development, UX, billing and go-to-market execution.
- Architected and shipped a multi-tenant platform with REST APIs, RBAC, CRM, billing and notifications, powering the manager dashboard, admin console, booking experience and iOS/Android applications.
- Led and mentored 7 software engineers, 1 DevOps engineer, 1 QA engineer and 1 UX/UI designer, while remaining hands-on across backend, frontend and product delivery.
- Built AI voice and chat agents using Python/FastAPI, OpenAI and Anthropic APIs, RAG, pgvector and tool calling; integrated Twilio, Google Calendar/Meet, Stripe and Firebase.
- Owned production infrastructure and automated delivery across separate environments using Docker, Nginx, GitHub Actions and Grafana; represented the company at accelerators and international startup events.
Selected stack: Python, FastAPI, Node.js, Vue 3, React/Next.js, React Native, PostgreSQL, Redis, Docker
Yavuz Ö.
Last position:
Full-Stack Developer – Practical Project Work at Sybarium Limited
Company in the industrial sector
Projects completed during retraining
- Rebuilt the company website from WordPress using a modern stack with Astro and TypeScript, deployed on Vercel (live at sybarium.vercel.app); replaced the legacy CMS with a faster, maintainable system.
- Reduced page load time by ~80% (from 5 s to under 1 s) through optimization, caching, and asset optimization.
- Developed n8n automation workflows that integrate several REST APIs and internal systems, saving more than 3 hours of manual work per week.
Ersin K.
Last position:
Founder & Lead Architect at ORBYNT / 7Style
- Full automation of the software development process: ticket analysis → AI coding agents → pull request → automated code review → deployment
- Multi-tenant architecture with 82 database models and real-time WebSocket monitoring
- Integration of 40+ AI tools with Claude & GPT
- Tech stack: React, TypeScript, Express.js, PostgreSQL, Redis, BullMQ
- Platform in productive use with paying customers
Ibrahim H.
Last position:
Senior Full Stack / AI Engineer at Punktum Digital GmbH
- Context: Healthcare and laboratory teams required faster document analysis, treatment-planning support, and reliable AI workflows for MR/VR-assisted operations.
- Contribution: Built the AI healthcare platform, model/agent workflows, VR-glasses deployment platform, REST APIs, Next.js/React interfaces, and CI/CD pipelines.
- Impact: Delivered a production-ready AI product foundation that improved clinical document review, supported laboratory automation, and made VR fleet deployment manageable across environments.
Tech: TypeScript, Next.js, Node.js, React, Java, Spring Boot, Python, PyTorch, TensorFlow, Docker, PostgreSQL, OpenAPI, GitLab, GitHub Actions.
Discover over 15,000 top freelancers
Statistics of experts using Redis
Aggregated from the professional profiles of matched freelancers.
Experience
15 years (Germany: 17 years)
Position duration
2.2 years (Germany: 2.8 years)
Positions per freelancer
9 (Germany: 11)
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Banking and Finance, Retail
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
93% (Germany: 90%)
Master's degree or higher
44% (Germany: 49%)
Certifications per freelancer
1 (Germany: 2)
Most common languages
English, German, Spanish
Speak two or more languages
96% (Germany: 97%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Berlin 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 in Berlin using Redis
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Redis 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 (95%)
- Banking and Finance (45%)
- Retail (36%)
- Education (35%)
- Media and Entertainment (31%)
- Automotive (29%)
- Energy (27%)
- Healthcare (27%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Redis does
Redis is an in-memory data store used when applications need very fast reads, writes and event handling. It supports strings, hashes, lists, sets, sorted sets, streams and geospatial data. Companies use it for caching, sessions, queues, rate limiting, leaderboards and real-time application state.
Core architecture
Redis keeps frequently accessed data close to the application, reducing pressure on relational and document databases. Persistence options allow data to be written to disk, while replication and Sentinel support availability and failover. Redis Cluster distributes data across nodes when a single instance is no longer enough.
Ecosystem and tooling
Strong Redis professionals work across application code, data design and operations. They commonly use:
- Redis Cluster, Sentinel and replication for resilient deployments
- Redis Streams and Pub/Sub for event-driven features
- TTLs, eviction policies and Lua scripts for controlled data access
- RedisInsight, monitoring tools and infrastructure automation
They also understand the client libraries and connection patterns used by languages such as Java, Python, JavaScript, Go and .NET.
When expertise matters
Companies bring in freelance Redis expertise when cache behavior is causing outages, database load is rising or a real-time feature must respond without delay. Specialists can review key design, memory usage, expiration rules and concurrency before these decisions become costly to change. In Berlin, Redis work may involve remote delivery or close collaboration with local product and infrastructure teams.
Typical deliverables
A Redis engagement may produce a cache strategy, session architecture, queue or stream design, migration plan, performance review or production runbook. Professionals can also integrate Redis with relational databases, message brokers, containers and cloud services. The right approach depends on consistency needs, traffic patterns, recovery objectives and the consequences of stale data.
How to assess specialists
Look for professionals who explain why Redis belongs in the architecture instead of treating it as a default database. Strong specialists can discuss cache invalidation, hot keys, memory fragmentation, persistence trade-offs and failure recovery in concrete terms. Ask for examples of observability, load testing and incident handling, then verify that their design covers security, access control and operational ownership.
Frequently asked questions
Before you brief your next project: the most common questions about Redis.
Redis is commonly used for caching, session storage, rate limiting, queues, leaderboards and real-time features. Its in-memory model makes it useful when an application needs low-latency access to frequently changing data.
Redis is optimized for fast access to key-value and structured in-memory data, while a relational database is designed for durable records, joins and transactional queries. Many systems use both: Redis handles temporary or frequently requested data, and the primary database remains the source of truth.
Redis deployments need different availability patterns depending on their failure and scaling requirements. Sentinel can help manage failover for replicated instances, while Redis Cluster distributes keys across nodes and is suited to workloads that need horizontal data or throughput scaling.
A strong Redis freelancer should understand application caching, database design, networking, observability and deployment automation. Experience with Docker or Kubernetes, cloud infrastructure, message queues and a relevant client library is useful because Redis rarely operates in isolation.
The required level of Redis expertise depends on the risk and scope of the work. A simple cache integration may need application-focused support, while clustering, migration, persistence or incident prevention calls for a specialist who has operated Redis in production-like conditions.
Redis projects are often well suited to remote collaboration because architecture reviews, configuration work and monitoring can be handled through shared repositories and observability tools. On-site sessions in Berlin can still help when teams need workshops, incident reviews or close coordination with product and infrastructure groups.
Ask a Redis specialist to explain key naming, expiration, eviction, cache invalidation, persistence and recovery choices for your workload. Quality work includes measurable acceptance criteria, monitoring, failure tests and clear ownership rather than only a fast integration.
A Redis implementation can become fragile if teams treat the cache as permanent storage, ignore memory limits or use broad key scans in production. Other risks include hot keys, stale data, unsuitable persistence settings and missing controls for authentication, network access and sensitive values.
The average hourly rate of freelancers in Berlin, Germany who have used Redis in their recent projects is 94 €, which corresponds to a daily rate of about 751 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Redis in their recent projects, 93% hold at least a Bachelor's degree and 44% hold at least a Master's degree.
On average, freelancers in Berlin, Germany who have used Redis in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Berlin, Germany who have used Redis in their recent projects are English (100%), German (87%), and Spanish (13%).
The most common industries among freelancers in Berlin, Germany who have used Redis in their recent projects are Information Technology (95%), Banking and Finance (45%), and Retail (36%).
The most common business areas among freelancers in Berlin, Germany who have used Redis in their recent projects are Information Technology (100%), Product Development (96%), and Quality Assurance (47%).
Main locations of FRATCH Experts, who have recently used Redis
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.
Hamburg 
Munich 
Cologne 
Frankfurt 
Stuttgart 
Dusseldorf 
Leipzig 
Dortmund Request a free demo
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Philipp Thomaschewski
FRATCH CEO
