Quality Engineer

Essential functions

Key Responsibilities

• Lead automation efforts to accelerate MineStar releases while maintaining high standards of quality and safety for mining operations.
• Define and implement MineStar-specific test strategies, metrics, and KPIs to assess product quality and release readiness.
• Build and maintain automation frameworks covering MineStar UI, APIs, services, and data flows.
• Integrate automation into CI/CD pipelines to enable continuous validation during MineStar modernization and re-platforming.
• Collaborate closely with Test Leads, Product Managers, System Architects, and Platform teams to align quality with MineStar''s target architecture.
• Mentor QA engineers (manual and automation) and support their transition to automation-first, quality-engineered practices.

Qualifications

• Strategy Leadership: Define and execute the end-to-end performance testing strategy, workload models, and NFR (Non-Functional Requirements) benchmarks for the MineStar platform.
• Testing at Scale: Design, script, and execute load, stress, endurance, spike, and scalability tests simulating high-concurrency, real-world site operations.
• Architecture Modernization: Validate system behavior, throughput, and latency during MineStars ongoing re-platforming and cloud/microservices transition.
• Continuous Performance (CI/CD): Integrate automated performance tests into CI/CD pipelines to catch performance regressions early in the development lifecycle.
• Root Cause Analysis Optimization: Partner with Architecture, Platform, and DB teams to analyze bottlenecks (CPU, memory leaks, thread locks, network latency, slow DB queries) and recommend actionable fixes.
• Mentorship Process: Mentor QA and development engineers on performance testing best practices, baseline monitoring, and performance-first engineering mindsets.

• Performance Tooling: Hands-on expertise with industry-standard performance testing tools (e.g., JMeter, Locust, Gatling, or Neoload).
• System Architecture: Proven experience testing microservices-based architectures, REST/gRPC APIs, event-driven systems (e.g., Kafka, RabbitMQ), and on-premise/hybrid cloud deployments.
• Monitoring APM: Deep experience with Application Performance Monitoring (APM) tools (e.g., Dynatrace, AppDynamics, Datadog, New Relic) and log analytics (Splunk, ELK stack).
• Database Protocol Validation: Strong ability to analyze database performance, write complex SQL queries, and diagnose slow-running queries and indexing issues.
• CI/CD Integration: Experience integrating performance scripts into modern build pipelines (e.g., Azure DevOps, Jenkins, GitLab CI).
• Agile Communication: Excellent communication and analytical skills, with a track record of collaborating with cross-functional, global teams to report performance metrics effectively.

• Leverage AI-assisted tools to optimize load distribution, accelerate workload model creation, analyze telemetry data, and automate root-cause detection for performance bottlenecks.
• Promote responsible, secure, and governed adoption of AI tools across performance engineering practices.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office