davit@portfolio:~
resume.pdf

Davit Mujirishvili

QA Automation Engineer

QA engineer with 4+ years of testing and automating financial exchange systems across trading, post-trade, clearing, and settlement.

location
Georgia (country) · UTC+4
Download PDF resume Email me

About

~/about/about.txt

I test the systems financial exchanges rely on after a trade is made: clearing, settlement, and everything in between. On Nasdaq exchange projects I have worked across APIs, user interfaces, FIX/FIXML messages, application logs, Linux environments, and databases, and I keep investigating a failure until I find its root cause.

Over the past year I have focused on test automation, developing 200+ end-to-end scenarios from scratch and contributing 350+ scenarios to a regression suite of 1,500+ tests. I also build practical tools that remove repetitive manual work: reference data preparation, trade submission, instrument generation, price loading, and Variation Margin calculations.

I work closely with developers, business analysts, and clients to clarify requirements, investigate root causes, and demonstrate what we build. I use Claude Code daily for automation development, debugging, and codebase analysis, and I share what I learn through tooling, documentation, and knowledge transfer sessions.

Experience

  1. /experience/nasdaq-asx

    Nasdaq ASX

    QA Engineer current     – present · 10 mos

    stack.txt

    • Browser DevTools
    • Claude Code
    • Cucumber
    • Gherkin
    • Java
    • Maven
    • Playwright
    • REST API
    • Swagger

    Automation

    • Develop and maintain automated end-to-end test coverage for complex post-trade, clearing, and settlement workflows using Playwright, Java, Maven, Cucumber, and Gherkin
    • Developed 200+ end-to-end scenarios from scratch, contributing to 350+ UI and API automation scenarios currently included in the regression suite
    • Build automation across UI and API layers, with approximately 50% UI and 50% API coverage, using Playwright and Java-based API automation
    • Automated critical ASX workflows including give-ups, take-ups, position netting, net and gross processing, closeouts, trade edits, trade cancellation, and physical delivery of futures and options
    • Contribute to a broader automated regression ecosystem containing 1,500+ automated tests, with the overall regression execution taking approximately 7 hours
    • Continuously improve automated scenarios by identifying edge cases and unexpected system behavior from test results, then extending the automation to ensure those cases are permanently covered by regression

    API testing

    • Automate and validate approximately 30 API endpoints covering authentication, reference data, pricing, configuration, market data, and core post-trade operations
    • Validate API response correctness, response times, throughput, data consistency, request/response contracts, and business rules across post-trade and settlement workflows
    • Use Swagger/OpenAPI to investigate endpoint behavior and validate API contracts before implementing automated coverage

    Tooling

    • Developed a high-volume price upload utility that retrieves approximately 50,000 assets through paginated API responses and posts market prices from source CSV data in ~5 minutes, replacing an otherwise impractical manual process
    • Developed an automated reference data collection utility that retrieves data from multiple API-accessible data sources and prepares JSON reference data for regression execution, replacing approximately 3 hours of manual preparation
    • Converted an existing Excel-based Variation Margin calculator into reusable Java logic, supporting calculations across 10 different product types and integrating the calculations directly into the automation workflow
    • Developed pre-regression automation for reference data preparation, market price loading, environment business date configuration, trading phase setup, and Variation Margin calculations, integrated directly into RegressionRunner.java and executed automatically as part of regression runs approximately 3 times per week

    Investigation

    • Diagnose automation failures using browser DevTools, API responses, application logs, and frontend/backend behavior to isolate defects and determine root causes

    Collaboration

    • Collaborate with developers and business analysts to clarify requirements, analyze acceptance criteria, identify edge cases, and translate business workflows into maintainable automated test scenarios

    AI-assisted engineering

    • Use Claude Code extensively as a daily AI-assisted engineering tool, applying it to approximately 70% of automation development work, including complex debugging, unfamiliar codebase analysis, test implementation, refactoring, API automation, Playwright development, troubleshooting, and engineering task decomposition
    • Use Claude Code as a development accelerator while reviewing, validating, debugging, and adapting generated solutions to ensure they meet project requirements and integrate correctly with the existing automation architecture

    Achievements

    • Identified approximately 15 defects through automated and exploratory validation while primarily focusing on expanding and maintaining automation coverage
  2. /experience/tvali

    Tvali

    QA Engineer current     – present · 11 mos

    stack.txt

    • Claude Code
    • CSS
    • Django
    • HTML
    • JavaScript
    • OpenAI API
    • PostgreSQL
    • Python
    • REST API

    projects.txt Tvali

    Product engineering

    • Lead QA and engineering activities for a production application built from scratch, covering Django, PostgreSQL, vanilla JavaScript frontend, REST APIs, authentication, payments, notifications, and analytics
    • Design and validate application architecture and business workflows across the full stack, from customer-facing UI and API endpoints to database operations and production behavior
    • Use Python and Django extensively for backend development and testing, while working directly with PostgreSQL and frontend technologies to investigate issues across application layers

    Features

    • Implement a role-based access control system supporting admin and moderator roles, with separate database schemas per user to enforce data isolation and protect tenant-specific data
    • Develop a complete appointment booking system, including configurable admin working hours, customer-facing booking pages, availability validation, booking workflows, and automated email/notification handling
    • Integrate the OpenAI API to build a bilingual AI assistant capable of answering platform-related questions in English and Georgian, including API integration, prompt handling, response processing, and application-level integration
    • Implement payment tracking and overdue monitoring, including payment status management, automated overdue identification, and auditability of financial operations
    • Develop audit logging and export functionality to maintain traceable records of important platform actions and support operational investigation
    • Build CSV-based bulk data workflows, supporting import and export operations for efficient administration of large datasets
    • Develop and maintain automated storefront generation, allowing platform users to generate customer-facing storefronts from configured business data
    • Implement and validate analytics dashboards for monitoring application and business activity

    Operations

    • Deploy and maintain the application in a production environment, handling configuration, authentication flows, email verification, application updates, and operational troubleshooting

    Testing

    • Perform continuous functional, integration, API, UI, database, regression, and exploratory testing throughout the development lifecycle, identifying issues early and validating fixes before production deployment

    AI-assisted engineering

    • Apply Claude Code and AI-assisted development extensively throughout the project to accelerate implementation, investigate unfamiliar technical problems, debug application behavior, develop features, refactor code, and automate repetitive engineering tasks
  3. /experience/nasdaq-tadawul

    Nasdaq Tadawul

    QA Engineer     – · 2 yrs 6 mos

    stack.txt

    • Bash
    • FIX Protocol
    • FIXML
    • Linux
    • Oracle Database
    • Python
    • SQL

    Testing

    • Performed end-to-end testing of several thousand FIX and FIXML test scenarios covering critical post-trade workflows within the Nasdaq Tadawul platform
    • Owned testing and regression analysis across the full trade lifecycle, including trade submission, allocation, aggregation, give-ups, take-ups, cancellation, settlement processing, and synchronization with the clearing engine
    • Executed and monitored 200+ automated smoke and regression pipelines, investigating failures across application, API, messaging, database, and infrastructure layers
    • Contributed to a regression framework containing several thousand FIX/FIXML scenarios, performing targeted maintenance and test updates within the repository while coordinating larger implementation changes with developers

    Investigation

    • Performed deep root cause analysis of failed regression scenarios by tracing transactions through FIX/FIXML messages, application behavior, GUI workflows, Oracle database state, and Linux server logs
    • Independently investigated failures to determine whether issues originated from the test implementation, application behavior, system infrastructure, or external dependencies, raising defects with developers or technical queries with project Business Analysts as appropriate
    • Used Oracle SQL and database investigation as part of regression failure analysis to verify persisted system state and identify discrepancies between expected and actual processing results

    Tooling

    • Developed 10+ Python and Bash automation utilities to eliminate repetitive QA tasks and improve testing efficiency across the team
    • Developed a Python/Bash trade submission utility that bypassed the traditional FIX engine workflow and allowed testers to submit trades directly to the clearing engine using a single command with configurable parameters such as instrument, quantity, and account
    • The trade submission utility replaced a complex multi-step process involving Linux server access, FIX engine configuration, batch activation, manual FIX message construction, and command-based submission, and became widely used across the QA team
    • Developed an automated instrument generation process for handling expired and replacement instruments, reducing a previously multi-day manual copy-and-paste process involving approximately 500 instruments to an automated Python/Bash workflow
    • Developed additional personal productivity utilities for large dataset investigation, API response ID matching, trade analysis, and test data handling, improving investigation speed during complex failures

    Operations

    • Performed Linux-based operational support including starting, stopping, and restarting systems, manually executing batches, rolling business dates, recovering failed processes, and retrieving application/server logs during testing and regression activities

    Knowledge sharing

    • Delivered 4 client-facing demonstrations introducing the testing framework, automation capabilities, and internal QA tooling to client stakeholders
    • Conducted 5+ internal knowledge transfer sessions, sharing system knowledge, testing approaches, automation utilities, and troubleshooting techniques with team members
  4. /experience/nasdaq-sgx

    Nasdaq SGX

    QA Engineer     – · 3 mos

    stack.txt

    • FIX Protocol
    • FIXML
    • PostgreSQL
    • SQL

    API testing

    • Performed end-to-end API testing of post-trade workflows using FIX and FIXML protocols, validating message processing and business outcomes across system components

    Data validation

    • Conducted PostgreSQL database validation to verify data persistence, consistency, and correctness throughout post-trade processing
    • Cross-validated API responses against database records to identify data discrepancies and verify end-to-end integrity across application layers

Projects

Skills

Education

~/education/bachelors-degree.txt

Bachelor's degree

institution
Tbilisi State University

~/education/languages.txt

Languages

  • Georgian
  • English
  • Russian

Certifications

~/certifications/certifications.txt

  • Postman: The Complete Guide - REST API TestingUdemy
  • The Complete Python Bootcamp From Zero to Hero in PythonUdemy
  • The Linux Command Line Bootcamp: Beginner To Power UserUdemy
  • HTML5 SpecialistAccredible ·

Contact