{ "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json", "basics": { "name": "Marharyta Halamuzdava", "label": "Performance & Software Quality Engineer — large-scale distributed systems", "email": "mhalamuzdava@gmail.com", "url": "https://cv.halamuzdava.com/", "summary": "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.", "profiles": [ { "network": "LinkedIn", "username": "marharyta-halamuzdava", "url": "https://www.linkedin.com/in/marharyta-halamuzdava/" } ] }, "work": [ { "name": "Palo Alto Networks", "position": "Staff Performance Engineer", "startDate": "2022-12", "endDate": "2025-04", "highlights": [ "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." ] }, { "name": "VISA Inc.", "position": "Senior Performance Engineer", "startDate": "2019-07", "endDate": "2021-04", "highlights": [ "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)." ] }, { "name": "EPAM Systems", "position": "Senior Performance Analyst", "startDate": "2016-02", "endDate": "2018-09", "summary": "Client: Wolters Kluwer", "highlights": [ "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." ] }, { "name": "EPAM Systems", "position": "Performance Analyst — Consultant", "startDate": "2015-11", "endDate": "2015-12", "summary": "Client: Thomson Reuters", "highlights": [ "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." ] }, { "name": "EPAM Systems", "position": "Performance Analyst", "startDate": "2014-12", "endDate": "2015-08", "summary": "Client: a customer in the travel domain", "highlights": [ "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." ] }, { "name": "EPAM Systems", "position": "Jr. Performance Analyst", "startDate": "2014-09", "endDate": "2014-10", "highlights": [ "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": [ { "institution": "Belarusian National Technical University", "area": "Industrial Engineering", "studyType": "Bachelor's Degree" } ], "skills": [ { "name": "Performance Testing", "keywords": [ "Apache JMeter", "Locust", "Pytest", "LoadRunner", "Custom Python load tooling", "Selenium WebDriver" ] }, { "name": "Profiling Diagnostics", "keywords": [ "JVM memory profiling & GC tuning", "Java Flight Recorder (JFR)", "Java Mission Control (JMC)", "YourKit", "AppDynamics", "Heap dump analysis", "MSSQL Profiler / SQL Profiler", "ANTS / dotTrace (.NET profilers)" ] }, { "name": "Observability Monitoring", "keywords": [ "Prometheus", "Grafana", "Splunk", "ELK (Elasticsearch/Logstash/Kibana)", "InfluxDB", "Kubernetes Dashboard", "SCOM / SquaredUP", "Perfmon", "Sysdig", "Fiddler" ] }, { "name": "Cloud", "keywords": [ "AWS (EC2, EKS, S3, RDS, Athena, Glue, Keyspaces, MSK, CloudWatch, OpenSearch)", "GCP (GKE, BigQuery, Pub/Sub, Cloud Monitoring, GCS)" ] }, { "name": "Databases Data", "keywords": [ "Apache Cassandra", "OpenSearch / Elasticsearch", "Google BigQuery", "MS SQL Server", "Apache Kafka / MSK" ] }, { "name": "CI CD Infra", "keywords": [ "Docker", "Kubernetes (incl. HPA)", "Helm", "Jenkins", "Terraform", "Gradle", "Git", "Linux (systems administration)" ] }, { "name": "Languages Scripting", "keywords": [ "Python", "Java", "Bash", "SQL", "Regular Expressions", "XPath / CSS selectors" ] }, { "name": "Methodology", "keywords": [ "Performance regression (E2E, CI-integrated)", "Capacity planning & modeling", "Bottleneck analysis (CPU/memory/GC/I/O/DB/network)", "Non-functional requirements & test planning", "High-load / distributed load generation (1K+ TPS)" ] } ], "meta": { "canonical": "https://cv.halamuzdava.com/resume.json", "version": "v1.0.0", "lastModified": "2026-11" } }