Performance test architect - Capital Market

Role: Performance Test Architect

Experience: 10+ Years

Location: Noida

Mandatory: Capital Market, Finance

JD:

Required Qualifications

• 10+ years of hands-on experience in performance testing and engineering for large-scale, distributed enterprise applications

• Deep expertise with load testing tools: JMeter, Gatling, and/or k6 — including scripting complex scenarios, correlation, parameterization, and custom plugins

• Strong experience with Kubernetes and Docker: understanding of pod scheduling, resource limits, HPA/VPA, and their impact on application performance

• Proven track record of building performance test frameworks integrated into CI/CD pipelines (Jenkins, GitLab CI, or GitHub Actions)

• Hands-on experience with monitoring and observability stacks: Grafana, Prometheus, ELK (Elasticsearch, Logstash, Kibana), or similar APM tools

• Solid understanding of database performance: SQL tuning, indexing strategies, connection pooling, and behavior under concurrent load (PostgreSQL, Oracle, or SQL Server preferred)

• Experience with message queue systems (RabbitMQ, Kafka, or ActiveMQ) and API performance testing (REST/gRPC)

• Proficiency in at least one programming language (Java, Python, or Go) for scripting, tooling, and automation

• Experience leading or mentoring a team of 2+ engineers in performance testing or related disciplines

Preferred Qualifications

• Domain experience in capital markets, financial services back-office operations, or reconciliation systems

• Experience performance testing shared-database architectures with multiple concurrent services

• Familiarity with Infrastructure-as-Code (Terraform, Ansible) and GitOps practices

• Experience with chaos engineering tools (Litmus, Chaos Monkey) for resilience testing

• Certifications in performance engineering (e.g., ISTQB Performance Testing, AWS/GCP/Azure certifications)

• Experience with financial data volumes: millions of positions/trades per reconciliation cycle

Key Responsibilities

Performance Test Lab & Infrastructure

• Design, build, and maintain a dedicated performance test lab that mirrors production Kubernetes environments (namespaces, resource quotas, network policies, storage classes)

• Provision and manage test infrastructure using Infrastructure-as-Code (Terraform, Helm charts) for repeatable, version-controlled environments

• Set up isolated test databases with realistic data volumes (millions of reconciliation records) and configure MQ/API test harnesses for inter-module communication

• Establish baseline hardware and configuration profiles for consistent benchmarking across releases

Test Strategy & Benchmarking

• Define the comprehensive performance test strategy covering load, stress, soak, spike, capacity, and scalability testing across all modules

• Create workload models based on real production traffic patterns — peak reconciliation windows, batch processing cycles, concurrent user simulations, and MQ throughput scenarios

• Establish KPIs and SLAs: response time percentiles (P50/P95/P99), throughput (TPS), resource utilization ceilings (CPU, memory, IOPS), reconciliation processing rates, and error thresholds

• Design module-level and end-to-end integration performance test suites that validate the shared database model under concurrent multi-module access

• Build automated benchmarking frameworks that produce comparable, versioned performance reports across releases

CI/CD Integration & Shift-Left Performance

• Embed performance test gates into Jenkins/GitLab CI/GitHub Actions pipelines so that every build is validated against performance baselines before promotion

• Implement automated regression detection: flag builds that degrade response times or throughput beyond configurable thresholds

• Create lightweight smoke performance tests for PR-level validation and full-scale suite execution for nightly/release pipelines

• Integrate with Grafana/Prometheus/ELK for real-time test execution dashboards, trend analysis, and alerting on performance anomalies

Analysis, Optimization & Collaboration

• Perform deep-dive root cause analysis of performance bottlenecks using profiling tools, APM traces, thread dumps, and database execution plans

• Partner with development teams to recommend and validate optimization strategies (query tuning, caching, connection pooling, async processing, horizontal scaling)

• Produce executive-level performance reports with clear findings, risk assessments, and capacity projections for product leadership

• Evaluate and benchmark database performance under the shared-DB model, including connection contention, lock analysis, and read/write throughput under concurrent module load

Team Leadership

• Recruit, mentor, and lead a team of 2–4 performance engineers, establishing best practices, coding standards, and review processes

• Drive a culture of performance awareness across engineering — conduct training sessions, brown-bags, and create internal knowledge base documentation

• Define career growth paths and skill development plans for the performance engineering team