Redis Expert in Switzerland
in minutes with vetted, available specialists matched by AIHire experts who design low-latency data layers, session stores and real-time features with Redis, Redis Cluster and Sentinel. FRATCH connects you with precise matches from vetted, available freelancers quickly.
Meet FRATCH Experts in Switzerland, who have recently used Redis
Mohamad K.
Last position:
Senior Backend Developer at Standing on Giants
- Led architecture and end-to-end engineering delivery for community-driven SaaS platforms serving 2M+ monthly active users.
- Architected and led the migration of a monolithic Python/FastAPI and PostgreSQL database and LangChain with codebase to an event-driven microservices architecture on AWS EKS, sustaining 10x traffic growth from ~150 RPS to 1,500+ RPS with zero re-architecture cycles.
- Defined and enforced engineering standards across services including API contracts, observability baselines, and deployment topology, reducing production incidents by 55% and MTTR from 2 hours to under 25 minutes within 9 months.
- Redesigned the caching and query layer using multi-tier Redis caching and database indexing/partitioning, cutting p95 API latency from 850ms to 180ms (78% reduction) and database CPU load by 45%.
- Built CI/CD platform on GitHub Actions, Terraform, and Kubernetes (EKS) with blue-green and canary rollouts, increasing deployment frequency from ~2/month to 8-12/day and reducing lead time from 10 days to under 6 hours.
- Implemented contract testing, automated load testing, and observability SLOs using Prometheus, Grafana, and OpenTelemetry, raising platform availability from 99.5% to 99.95% (10x reduction in error budget burn).
- Led and grew a cross-functional team of 8 engineers across backend, frontend, and DevOps, scaling headcount from 4 to 8 with 85% retention; owned hiring, onboarding, performance reviews, and career development.
- Partnered with Product, Design, and Client Success leadership as primary technical decision-maker; translated business goals into technical roadmaps and drove build-vs-buy decisions on authentication, search, and AI tooling.
- Introduced AI-assisted development workflows including automated code review and a RAG-based internal knowledge assistant using Graph (GraphRAG, Neo4J), increasing sprint throughput by 30% across two quarters.
- Owned incident command and production support rotation; established runbooks, postmortem culture, and on-call SLOs, reducing weekend paging incidents by 70%.
- Developed and optimized Algorithms using python libraries like Numpy and Pandas.
Christoph P.
Last position:
ICT DevSecOps Engineer & Security Coordinator at Abraxas Informatik AG
- Interface role with the SOC team; improved incident response time by 45% through structured escalation processes and proactive security monitoring.
- Defined technical standards for a multi-tenant enterprise platform (10+ services), resulting in a 30% shorter onboarding time for new clients in the public sector.
- Active knowledge transfer and mentoring of a 6-person team; increased team autonomy and established a sustainable engineering culture.
- Reduced time to market by 50% by optimizing CI/CD pipelines and establishing self-service deployments.
- Stack: GitLab CI/CD, Kubernetes, Nexus, Harbor, ArgoCD, HashiCorp Vault, Grafana, Python, PostgreSQL, Java, Spring Boot, Flyway, Quarkus, JBoss, Loki, Go, Kafka, Kustomize, MongoDB
Robin O.
Last position:
Co-Founder & AI Solutions Architect at airdys
- Product strategy, architecture, and technical co-direction
- AI workshops, client onboarding and go-to-market activities
- Design and implementation of AI architectures (LLMs, RAG, MCP, agents, voice, automation)
- Hands-on development of prototypes and production-ready AI integrations
- Consulting clients on AI adoption, workflows, and integration into existing infrastructure
- Collaboration with co-founders on strategic direction
- Collaboration in sales and customer acquisition
Tools and Technologies: OpenAI, Anthropic, Azure, Vercel AI SDK, RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol), FastAgent, VAPI, n8n, make.com, LibreChat, PostgreSQL, OpenAPI, Next.js, Vercel, Docker
Peter S.
Last position:
Web Application Developer PHP / WordPress Plugin Development at Gemeinde Bauma
- Analysis, consulting, and development of a WordPress application for the digital processing and delivery of the Bauma chronicle archive
Stefan H.
Last position:
Fullstack Development, Product Owner & Tech Lead at Trex AG
- Business analysis, architecture, and implementation of a telemedicine platform for pet owners.
- Leading the development team as Product Owner and Tech Lead.
- Introducing agile processes, setting up development guidelines and system documentation.
- Planning and implementing features like video calls, live chat, and marketing automation.
- Implementing AI-based features such as automated tagging of information (missing pet reports, marketplace entries, etc.), preparation of social media content, and processing of conversation transcripts.
- Skills: Angular, NGXS, Tailwind, Java, Spring Boot, Kubernetes, Docker, CI/CD, MySQL, LLMs, RAG, MCP, Redis, OpenSearch.
- Industry: Veterinary medicine.
Matthias I.
Last position:
Fractional CTO (Principal Engineer / Technical Architect)
- Designed large-scale systems and APIs serving thousands of concurrent users.
- Refactored a 650k-LOC monolith and led full AWS migration for stable performance.
- Introduced SLO-based observability, improving reliability and recovery flow.
- Optimised cloud and databases, achieving significant cost and latency reduction.
- Delivered LLM, RAG, and document-automation pipelines adopted in production.
Georgios S.
Last position:
Senior Software Engineer at UBS Bank
- Implementations of a code refactoring framework able to refactor thousands of repositories leveraging Generative AI
- Use Python (Django, Flask, FastAPI), Java and Typescript in Azure Cloud (Data Lake, VMs, AI) and GitLab infrastructure
- Mentoring and pair programming
- Obtained Azure AI-900 and AI-102 certifications
Alejandro A.
Last position:
AI Researcher & Engineer at Tufa Labs
- Deployed and optimized the inference stack on a multi-node DGX B200 cluster across vLLM and SGLang (serving, throughput and latency tuning).
- Built, with a small team, an internal Python library for LM pretraining covering the full training loop: distributed training with PyTorch FSDP, data pipelines, checkpointing, config and hyperparameter management, and experiment tracking.
- Built and evaluated agent scaffolds on interactive game benchmarks similar to ARC-AGI-3, with metrics for how models plan, explore and adapt across multi-step episodes; classified model errors and fed the findings back into scaffold and evaluation design.
- Researched looped transformer architectures.
Ned O.
Last position:
Tech Lead at R3leaf GmbH
- Autonomously drafted architecture and delivered production code at startup pace
- Wrangled diverse geospatial formats (NETCDF, GeoTIFF, GML) into unified standards and built scalable climate data visualisations from hundreds of GBs of geodata in a production web app
- Mentored developers, facilitated AI skill sharing, and contributed to competitive strategy with C-Level leadership
Karl E.
Last position:
incl. CI/CD, automation at AALS Software AG
- Designed and delivered a practical real-time course on Flink and Hadoop with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, and Kafka
- Gained extensive DevOps and CI/CD experience
- Created ETL/ELT pipelines with Apache tools and Pentaho
- Led projects in municipal software, financial services, and big data with Kafka
- Developed AI/NLP models and chatbots with RASA, Chatter, and Dialogflow
- Built and managed a TypeDB knowledge database
- Worked with OpenStack, Kubernetes, and Podman
Christoph J.
Last position:
Project management, Software engineering, Software architect, DevOps at Migros Genossenschafts Bund
- Greenfield project M-Zollmanager: Development of an internal platform to support users in booking requirement areas on line items in assessment notices.
- Greenfield project M-Deliveryplan: Development of an internal platform for planning and tracking deliveries in the international transport sector.
- Created functions to predict the estimated arrival time of container ships and goods from the port of loading to the port of destination, considering potential events.
- Developed the TrackAndTrace add-on for M-Deliveryplan to track and plan goods and containers.
- Built a generic AI chatbot for Migros app infrastructure, including ChatGPT integration and creating AI workflows with N8N.
- Developed AI assistants to automate repetitive tasks, such as creating release notes or processing Jira tasks based on N8N workflows.
- Further development and maintenance of the M-LFS, M-Vehicleaccess and M-Worklog apps.
- Used C#, Angular 18, DevOps practices, N8N, Kubernetes, Docker, Jira, Confluence and Azure.
- Ongoing project with continuous development of platforms and workflows.
Milica M.
Last position:
Full-Stack Developer at Holycode
- Contribute to a cross-functional team building a cloud-based bookkeeping platform for SMEs
- Design and implement Java Spring Boot microservices with clear separation of concerns
- Integrate core services via REST and gRPC APIs
- Implement event-driven workflows using RabbitMQ for reliable, decoupled messaging
- Model and manage transactional data in PostgreSQL and leverage Redis for caching
Discover over 15,000 top freelancers
Statistics of experts using Redis
Aggregated from the professional profiles of matched freelancers.
Experience
21 years
Position duration
1.9 years
Positions per freelancer
13
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Education
Certification focus areas
Information Technology, Product Development, Business Intelligence
Bachelor's degree or higher
100%
Master's degree or higher
67%
Doctorate
22%
Certifications per freelancer
2
Most common languages
English, German, Spanish
Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Switzerland 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 Switzerland 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 19 Sep 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 (100%)
- Banking and Finance (83%)
- Education (67%)
- Professional Services (50%)
- Healthcare (42%)
- Retail (42%)
- Energy (33%)
- Manufacturing (25%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
In-memory data layer
Redis is an in-memory data store used for fast reads, writes and event-driven workloads. It supports strings, hashes, lists, sets, sorted sets and streams, making it useful for caching, sessions, queues, rate limiting and real-time applications. Data can also be persisted when a workload needs recovery beyond memory.
Where Redis fits
- Accelerate database-heavy web applications with application caching
- Store user sessions, tokens and short-lived state
- Power leaderboards, counters, presence and live dashboards
- Coordinate background jobs and lightweight message flows
- Build autocomplete, recommendation and feature-flag services
Redis often sits beside PostgreSQL, MySQL, MongoDB or Elasticsearch rather than replacing the primary system of record. Its role depends on access patterns, consistency needs, retention and recovery requirements.
Ecosystem and tooling
Professionals work with Redis clients for languages such as Java, Python, JavaScript, Go, PHP and .NET. They may use Redis Cluster for horizontal scaling, Sentinel for high availability, Streams for event processing and modules such as RediSearch or RedisJSON for specialized data access. Monitoring, persistence settings, eviction policies and connection pooling are part of the wider toolkit.
When expertise matters
Companies bring in freelance Redis specialists when a cache becomes a bottleneck, production latency changes unexpectedly or a real-time feature needs a dependable data design. Expertise is also valuable during migrations, architecture reviews, incident response and performance tuning. Teams in Switzerland may choose remote collaboration, on-site workshops or a hybrid setup, depending on security and delivery needs.
What strong professionals deliver
- A data model aligned with commands, key access and expiration behavior
- Clear separation between cache data, durable data and transient state
- Cluster, replication and failover plans tested under realistic load
- Observability for memory use, hit rates, latency and slow commands
- Safe rollout, backup and recovery procedures
Strong specialists understand that fast responses do not compensate for poor invalidation or uncontrolled memory growth. They document key naming, serialization, time-to-live rules and failure behavior so application teams can operate the system confidently.
Choosing the right specialist
Look for evidence of production work with the Redis features your system actually needs, not only a familiar product name. Ask how the professional would handle cache stampedes, hot keys, eviction, persistence, failover and data loss. They should also be comfortable tracing behavior across application code, databases, containers, cloud infrastructure and monitoring tools. For Swiss teams, confirm communication language, working hours and access procedures before the engagement begins.
Frequently asked questions
Quick answers to the questions that come up most around Redis.
Redis is commonly used for caching, session storage, rate limiting, queues, counters and real-time features. It is valuable when applications need quick access to changing data, but it should not automatically replace a durable primary database.
Redis offers richer data structures, persistence options, replication and features such as Streams. Memcached can be a simpler choice for basic caching, while the better option depends on required durability, operations and data access patterns.
Redis work is closely connected to application architecture, SQL or NoSQL databases, messaging, container deployment and observability. Strong professionals also understand concurrency, network behavior, serialization, security and the failure modes of distributed systems.
Redis experience should match the risk and complexity of the workload. A cache for a contained application may need focused implementation skills, while clustered production systems require proven knowledge of replication, persistence, failover, memory management and incident response.
Redis projects can often be delivered remotely when the team has secure access, clear runbooks and suitable monitoring. On-site sessions can still help with architecture workshops, regulated environments or incident preparation, and Swiss teams should agree on language and collaboration hours early.
Redis is a strong option when the application needs flexible data structures, shared state, precise expiration or real-time coordination across services. A built-in database cache may be simpler when the workload is tightly coupled to one database and does not need Redis-specific behavior.
Redis quality is shown by clear reasoning about data models, key design, expiration, memory limits and recovery. Ask for an explanation of how the professional would prevent hot keys, cache stampedes, unsafe invalidation and silent data loss in your specific system.
Redis deployments using Cluster and Sentinel solve different operational problems. Cluster distributes data across nodes, while Sentinel monitors instances and supports failover; specialists should explain topology, client behavior, consistency trade-offs and how the team will test recovery.
The average hourly rate of freelancers in Switzerland who have used Redis in their recent projects is 101 €, which corresponds to a daily rate of about 808 € based on an 8-hour working day.
Of the freelancers in Switzerland who have used Redis in their recent projects, 100% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 22% hold a doctorate.
On average, freelancers in Switzerland who have used Redis in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Switzerland who have used Redis in their recent projects are English (100%), German (83%), and Spanish (42%).
The most common industries among freelancers in Switzerland who have used Redis in their recent projects are Information Technology (100%), Banking and Finance (83%), and Education (67%).
The most common business areas among freelancers in Switzerland who have used Redis in their recent projects are Information Technology (100%), Product Development (100%), and Project Management (58%).
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.
Zurich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
