Performance and software-quality engineer with 9+ years testing and optimizing large-scale distributed systems. Deep across system architecture, network, and databases, with a broad monitoring/profiling toolset — and a habit of automating the analysis itself to cut investigation time and sharpen insight.

Focus areas

Performance Engineering

End-to-end performance regression, load modeling, and bottleneck analysis on distributed systems — JVM/GC tuning, DB and query optimization, capacity models.

Performance & Reliability

Production performance ownership: autoscaling, load-balancer and health-check tuning, monitoring/alerting with Prometheus, Grafana, Splunk, and the ELK stack.

Performance Automation

Automating the analysis itself — CI-integrated performance regression, data generation/cleanup at high volume, and reusable frameworks in Python, Java, Bash.

Experience

2022-12 — 2025-042 y 5 m

Staff Performance Engineer

Palo Alto Networks

  • Optimized database and search performance (OpenSearch, Cassandra, BigQuery) through data-node configuration and query optimization.
  • Implemented Kubernetes Horizontal Pod Autoscaling (HPA) in production, yielding significant infrastructure cost reduction.
  • Guided major platform migrations — application move to GCS and BigQuery, AWS Keyspaces → Cassandra, AWS MSK → hosted Kafka, and Spring Boot / Java / MSK upgrades — analyzing regression risk and preventing critical performance issues through early detection and proposed fixes.
  • Designed and implemented end-to-end performance regression and integrated it into the CI pipeline (including Python data-generation and cleanup for high-volume environments), cutting level-of-effort and making the suite runnable by other teams.
  • Performed JVM memory profiling and optimization — resolving leaks, cache mismanagement, and high-utilization issues.
  • Established integrated monitoring across Splunk, OpenSearch, Kibana, and Grafana; built advanced performance dashboards with Prometheus and InfluxDB and a comprehensive metrics-tracking and alerting system.
2019-07 — 2021-041 y 10 m

Senior Performance Engineer

VISA Inc.

  • Developed capacity models through systematic analysis of application performance patterns and resource utilization, and architected monitoring strategies from detailed study of customer applications and infrastructure diagrams.
  • Analyzed execution plans to find MSSQL query bottlenecks and optimized them through rewriting and indexing of complex queries, reducing overall latency by 40%.
  • Fixed uneven traffic distribution by tuning load-balancer configuration and health-check parameters — reducing latency, improving resource utilization across service pods, and increasing system stability.
  • Eliminated OutOfMemory errors by tuning generation ratios, expanding metaspace limits, and sizing the heap to usage patterns; optimized garbage collection by benchmarking multiple GC algorithms and applying the best configuration.
  • Built automated performance data-collection and analysis frameworks in Java and Bash, significantly reducing manual effort.
  • Applied CPU, memory, and bus-architecture knowledge to performance characterization and software optimization, improving system performance for hardware components (CPU / memory / disk).
2016-02 — 2018-092 y 8 m

Senior Performance Analyst

EPAM Systems · Client: Wolters Kluwer

  • Transformed the performance-testing process — realistic system-load scenarios plus an automated testing framework — cutting release cycles from ~10 days to ~3 days with higher quality and improved reliability, and a stronger ability to predict and prevent performance issues.
  • Mentored and onboarded a junior performance engineer across a stream of 10+ complex independent products, structuring the knowledge-transfer and mentoring strategy and growing them to an independent contributor within 3 months.
  • Continuously expanded testing scope to new applications and features, defined non-functional performance requirements, and authored technical test plans surfacing benefits and risks.
  • Led performance-results overviews — technical summaries for the engineering team and historical trend/improvement summaries for the business team.
  • Automated test-data generation in Java and built batch scripts for integration testing of Java applications; developed and maintained JMeter scripts and ran distributed load generators for high-load tests at 1K+ TPS against AWS and on-premise environments.
2015-11 — 2015-122 m

Performance Analyst — Consultant

EPAM Systems · Client: Thomson Reuters

  • Consulted on improving the existing performance-testing strategy using domain best practices — reviewing PoCs, Confluence structure, result reports, tooling, and methodology — and delivered a detailed process-overview presentation with a list of recommendations.
  • Tracked adoption of the recommendations, shared constructive feedback, and supported effective cross-team communication.
2014-12 — 2015-089 m

Performance Analyst

EPAM Systems · Client: a customer in the travel domain

  • Defined performance requirements from Google Analytics production usage, designed and built JMeter workload models/simulations to test XML-based web services, established performance and scalability benchmarks, analyzed results to identify bottlenecks, and led results overviews for dev/DB engineers and managers.
  • Found the root cause of the slowest transactions through MS SQL database profiling and recommended procedure and index optimizations.
  • Ran demo sessions and shared performance-testing knowledge with the development team, cutting feedback time.
2014-09 — 2014-102 m

Jr. Performance Analyst

EPAM Systems

  • Developed a parameterized JMeter script to load a SOAP web service and identified system metrics and service capacity.
  • After spotting high CPU usage, performed .NET code profiling to locate hot spots; the resulting algorithm optimization increased service capacity 10×. Also compared profiling tools and shared trade-offs with the team (adopting ANTS Profiler).
  • Identified functional and web-service configuration issues during performance testing and collaborated closely with developers on detailed, reproducible reports — roughly halving the issue-fixing time.

Education

  • Belarusian National Technical University — Bachelor's Degree — Industrial Engineering

Connect

  • Emailmhalamuzdava@gmail.com
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