Redis Engineer (RTS Redis)
GSSTech Group
Posted: February 16, 2026
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Quick Summary
An experienced Redis Engineer with strong hands-on experience in Redis administration, including dump, persistence, and performance optimisation, is required for this role.
Required Skills
Job Description
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.
Required Skill Set
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
Other Details
• Banking domain knowledge: Not mandatory
• Experience Level: 5–8 years preferred
• Deployment: Immediate