Job Title: Resilience, Testability & Scalability Lead Location: Fort Mill, SC / New York / New Jersey /(Hybrid) Key Responsibilities: • Design and implement high availability and failoverstrategies acrossmulti-zone AWS deployments • Lead the development and execution of disaster recovery and business continuity plans ,including RTO/RPO validation and cross-region strategies • Define testability strategies, test data management frameworks,and performance testing protocols • Enable infrastructure and application resilience by introducing circuit breakers, retry patterns, service meshes ,and graceful degradation mechanisms • Establishreal-timemonitoring, alerting,and logaggregation frameworks using tools like Cloud Watch and Prometheus • Drive test automation and quality engineering best practices, integrating withCI/CD pipelines • Optimize application and data layer performance through querytuning, caching, and indexing strategies • Scale data processing using distributed frameworks like Apache Spark,and implementevent-driven streamprocessing with Kafka • Collaborate with platform, DevOps, and SRE teamstoensure resource efficiency, cost control, and performance SLAs • Contribute toregulatory readiness by enforcing security, encryption, and audit logging standards Required Skills Experience: • Infrastructure Resiliencies DR: • Multi-AZ deployments, auto-scaling, load balancing, circuit breakers • Disaster recovery design: backup/restore, cross-region replication, RTO/RPO • Monitoring Observability: • Experience with Cloud Watch, Prometheus us, log aggregators • Setup alerting for incident response, latency, through put, and error rates • Application Resilience Security: • Error handling, service degradation, exponential back off • Security best practices: I AM policies, encryption Trest/transit • Familiarity with FINRA/SIP Compliance standards(preferred) Test Automations Quality: • Unit testing(e.g.,pytest),integrationtesting,E2E automation • Test data generation, synthetic data, environment provisioning • Performance testing using J Meter, Gatling, stress and capacity testing • Code reviews, static analysis, data validation, anomaly detection • Scalability Optimization: • Horizontal scaling using Kuber netes, Docker, service discovery • API Gateway, caching layers (Redis, Memcached),DB partitioning • Connection pooling, capacity planning, cost-aware architecture Datas Stream Processing: • Spark cluster management, parallel processing, bigdata optimization • Kafka-based messaging, windowing, and aggregation for real- time data