Select your current position
Pick a role and level — we'll show the growth path, skills and gap analysis.
Development path
Junior
0-2 years
Responsibility: Writing load testing scripts. Running tests by scenarios. Collecting metrics. Preparing results reports.
Key skills:
Middle
2-5 years
Responsibility: Designing load scenarios. Bottleneck analysis. Metric correlation (CPU, memory, DB). CI/CD integration.
Key skills:
Senior
5-8 years
Responsibility: Performance testing architecture. Chaos engineering. Capacity modeling. Application profiling. Optimization recommendations.
Key skills:
Lead / Staff
7-12 years
Responsibility: Performance engineering strategy. SLA/SLO for performance. Coordination with development and SRE.
Key skills:
Principal
10+ years
Responsibility: Enterprise performance strategy. Performance culture. Capacity planning at scale.
Key skills:
Gap analysis: skills to develop
To reach the next level you'll need to develop:
Independently develops Chaos Engineering tests. Applies test design techniques. Integrates tests into CI/CD. Covers edge cases.
Conducts E2E performance testing: full user journey performance, multi-service latency, end-to-end throughput. Tests with realistic data volumes.
Conducts load testing: ramp-up, steady state, peak load scenarios. Uses k6/Gatling: custom metrics, thresholds, checks. Analyzes: throughput, latency, error rate, resource usage.
Understands TCP/IP stack behavior under load — analyzes connection pooling, keepalive settings, and socket exhaustion. Configures TLS/SSL for performance impact assessment. Works with load balancers and reverse proxies to test traffic distribution. Understands DNS resolution timing and TTL impact on test results. Debugs network bottlenecks using tcpdump and Wireshark analysis.
Applies the test pyramid for performance: micro-benchmarks (unit level), component load tests (integration), full system tests (E2E). Determines optimal distribution.
Manages test data for performance: realistic data volumes, data distribution matching production. Generates synthetic data. Ensures data isolation between test runs.
Manages performance test environments: dedicated resources, network isolation, baseline configuration. Ensures consistent results: resource monitoring, noise reduction.