Infrastructure Engineer

Weave

3 - 8 years

6 - 10 Lacs

kolkata mumbai new delhi hyderabad pune chennai bengaluru

Posted:5 hours ago| Platform:

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Skills Required

computer science backend automation testing tools mysql disaster recovery debugging open source information technology monitoring

Work Mode

Work from Office

Job Type

Full Time

Job Description

Infrastructure Scaling & Optimization:
Analyze current infrastructure and design solutions to handle increasing load with high availability.
Database Performance Tuning:
Optimize MySQL (indexes, queries, partitioning, replication, sharding) and Redis caching strategies for throughput and latency improvements.
Message Queue Scaling:
Enhance and optimize
ActiveMQ
for large-scale, distributed messaging with high durability and reliability.
Server & Application Scaling:
Tune
Jetty Spark servers
for concurrency, session management, load balancing, and failover strategies.
Monitoring & Bottleneck Detection:
Implement monitoring dashboards (Grafana, Prometheus, ELK/EFK, or Azure Monitor) to detect slow queries, CPU/memory bottlenecks, and scaling issues.
Distributed Systems Reliability:
Ensure fault tolerance, disaster recovery, and horizontal scaling strategies.
CI/CD & Automation:
Work with GitHub Actions, Jenkins, or Azure DevOps for automated deployments and scaling workflows.
Collaboration:
Partner with backend engineers, DevOps, and product teams to deliver reliable infrastructure that meets performance goals.

What You Will Need to Accomplish the Job

Bachelor s degree in
Computer Science, Information Technology, or related field
.
3+ years of experience
in scaling infrastructure for distributed systems or high-traffic applications.
Strong hands-on experience with:
- Databases:
  MySQL (query optimization, replication, partitioning, indexing strategies).
- Caching:
  Redis (cluster setup, pub/sub, eviction policies, memory optimization).
- Message Queues:
  ActiveMQ (scaling consumers/producers, HA clusters, performance tuning).
- Web Servers:
  Jetty with Spark framework (thread pools, tuning JVM, load balancing).
Proficiency in
monitoring & observability tools
(Grafana, Prometheus, ELK/EFK stack, Azure Monitor, or DataDog).
Knowledge of
distributed systems principles
(CAP theorem, sharding, replication, consensus).
Familiarity with
CI/CD pipelines, Docker, Kubernetes (AKS/EKS/GKE optional)
.
Strong problem-solving skills in debugging production performance bottlenecks.
Ability to work
independently and collaboratively
in a fast-paced environment.

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