Design, deploy, and maintain RTS Redis (Redis TimeSeries) for real-time analytics. Implement caching, persistence, pipelines, and performance optimizations. Deploy Redis on OpenShift, integrate with Python and DevOps toolchains, explore vector DB and AI-driven caching, and collaborate with development teams to ensure scalable, highly available Redis solutions.
Role Overview
We are looking for an experienced Redis Engineer with in-depth knowledge of RTS Redis (Redis TimeSeries) for real-time data processing and caching operations. The ideal candidate will possess strong hands-on experience in Redis administration, including dump, persistence, and performance optimisation, with the ability to deploy and manage Redis solutions within OpenShift environments.
A developer mindset and solid understanding of Redis data structures, pipeline management, and AI integration are essential for this role.
Key Responsibilities- Design, configure, and maintain RTS Redis (Redis TimeSeries) databases to support real-time analytics and time-series data workloads.
- Implement caching, dump, and persistence mechanisms to ensure data durability and performance.
- Develop and manage Redis pipelines, primarily focusing on Redis databases while leveraging other databases where beneficial.
- Deploy Redis environments in OpenShift with focus on scalability, high availability, and fault tolerance.
- Integrate RTS Redis solutions with Python and DevOps toolchains for automation and monitoring.
- Optimise Redis memory usage, query performance, and overall system reliability.
- Collaborate with development teams to integrate Redis into microservices and application architecture.
- Explore Vector Database integrations and AI-driven caching models to enhance performance.
Primary Skills:
- Redis Administration (RTS Redis / Redis TimeSeries)
- Real-time Data Processing
- Caching, Dump, and Persistence
- Immediate Deployment and Configuration Skills
Additional Skills:
- Python
- DevOps
- OpenShift
Preferred Combination:
- RTS Redis + OpenShift Deployment Experience
Good to Have:
- Knowledge of Vector Databases (e.g., Pinecone, Milvus, Weaviate)
- Exposure to AI model caching and data management
- Experience with CI/CD automation for Redis-based workloads
- Banking domain knowledge: Not mandatory
- Experience Level: 5–8 years preferred
- Deployment: Immediate
Top Skills
Ai Integration
Ci/Cd
DevOps
Milvus
Openshift
Pinecone
Python
Redis
Redis Timeseries (Rts Redis)
Vector Database
Weaviate
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