System Performance Expert / Site Reliability Engineer – TEMPORARY ALLOCATION (1s
GlobalLogic, Poland, NY, United States
System Performance Expert / Site Reliability Engineer – TEMPORARY ALLOCATION (1st November 2026) IRC294203
Our client is a leading workforce and human capital management SaaS provider, supporting hundreds of thousands of healthcare workers across the U.S. The role focuses on ensuring optimal system performance for a real‑time, data‑driven platform that helps providers manage workforce, quality, and regulatory compliance.
Requirements
Optimizing Redis caching and SQL queries (including indexing, query plans, and concurrency control)
Network optimization (compressing front‑end assets, minimizing payload size)
Performance testing at scale (load, stress, soak testing; identifying bottlenecks under peak conditions)
Fine‑tuning for scalability (horizontal scaling, load balancing, partitioning/sharding strategies)
Asynchronous processing (job queues, batch processing, event‑driven architectures)
Database performance tuning (connection pooling, replication, failover strategies)
Observability (metrics, logging, tracing, APM tools) to proactively detect and resolve issues
Following strict governance on PII data
Experience with agentic tools is a plus, but not required.
Job Responsibilities
Identify and resolve performance bottlenecks across front‑end and large‑scale background processes such as payroll runs.
Optimize I/O and system scalability to support peak workloads.
Design and execute load, stress, and soak tests to validate performance goals.
Implement caching, queueing, and database tuning strategies that improve response times.
Collaborate with cross‑functional teams to implement and monitor observability tooling.
Ensure compliance with data governance requirements, particularly for PII data.
Qualifications
5–10 years of professional experience in performance engineering, site reliability, or related fields.
Strong knowledge of Azure SQL Database, Redis, and performance tuning techniques.
Proficiency with monitoring and observability tools such as metrics dashboards, logging, and tracing.
Experience managing distributed systems at scale, including scalability and fault‑tolerance strategies.
Excellent problem‑solving skills and ability to work independently with minimal supervision.
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Our client is a leading workforce and human capital management SaaS provider, supporting hundreds of thousands of healthcare workers across the U.S. The role focuses on ensuring optimal system performance for a real‑time, data‑driven platform that helps providers manage workforce, quality, and regulatory compliance.
Requirements
Optimizing Redis caching and SQL queries (including indexing, query plans, and concurrency control)
Network optimization (compressing front‑end assets, minimizing payload size)
Performance testing at scale (load, stress, soak testing; identifying bottlenecks under peak conditions)
Fine‑tuning for scalability (horizontal scaling, load balancing, partitioning/sharding strategies)
Asynchronous processing (job queues, batch processing, event‑driven architectures)
Database performance tuning (connection pooling, replication, failover strategies)
Observability (metrics, logging, tracing, APM tools) to proactively detect and resolve issues
Following strict governance on PII data
Experience with agentic tools is a plus, but not required.
Job Responsibilities
Identify and resolve performance bottlenecks across front‑end and large‑scale background processes such as payroll runs.
Optimize I/O and system scalability to support peak workloads.
Design and execute load, stress, and soak tests to validate performance goals.
Implement caching, queueing, and database tuning strategies that improve response times.
Collaborate with cross‑functional teams to implement and monitor observability tooling.
Ensure compliance with data governance requirements, particularly for PII data.
Qualifications
5–10 years of professional experience in performance engineering, site reliability, or related fields.
Strong knowledge of Azure SQL Database, Redis, and performance tuning techniques.
Proficiency with monitoring and observability tools such as metrics dashboards, logging, and tracing.
Experience managing distributed systems at scale, including scalability and fault‑tolerance strategies.
Excellent problem‑solving skills and ability to work independently with minimal supervision.
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