Perform hands-on functional, integration, regression, and end-to-end testing, design test strategies and plans for banking business workflows, and coordinate offshore team activities.
Responsibilities
Perform hands-on functional, integration, regression, and end-to-end testing
Design Test Strategy, Test Plan, estimate and track testing efforts, develop, review, and execute detailed test scenarios and test cases based on functional requirements and banking business workflows
Actively participate in and coordinate defect triage, collaborating with developers, business analysts, and Testing teams to investigate, prioritize, and resolve defects
Perform defect retesting, regression validation, and root cause investigation to ensure quality fixes
Support test data preparation, test environment validation, and troubleshooting of testing dependencies
The Business Analyst / Quality Assurance Analyst – Advanced performs both BA and QA functions, gathering requirements from stakeholders, conducting requirements analysis, and completing comprehensive software testing within a collaborative Agile environment.
Responsibilities
Gather, analyze and refine business and technical requirements, user stories, use cases and acceptance criteria.
Map business processes and workflows; prepare functional specifications, diagrams, reports and user documentation.
Evaluate existing practices, system capabilities and controls; recommend improvements and resolve requirement gaps.
Translate policy and operational needs for technical teams and explain technical changes to business stakeholders.
Develop and execute test plans, test scripts and test cases for new or modified software, including regression and integration testing.
Requirements
Bachelor's degree in business, information systems, computer science or a related field, or equivalent extensive relevant experience.
Lead functional, integration, regression, and end‑to‑end testing for banking applications, design test strategy, coordinate defect triage, and support test data and environment management.
Responsibilities
Perform hands‑on functional, integration, regression, and end‑to‑end testing
Design Test Strategy, Test Plan, estimate and track testing efforts, develop, review, and execute detailed test scenarios and test cases based on functional requirements and banking business workflows
Actively participate in and coordinate defect triage, collaborating with developers, business analysts, and Testing teams to investigate, prioritize, and resolve defects
Perform defect retesting, regression validation, and root cause investigation to ensure quality fixes
Support test data preparation, test environment validation, and troubleshooting of testing dependencies
Responsible for end‑to‑end testing of voice journeys across markets and configurations, including automated and manual testing of speech recognition, output, and conversational AI.
Responsibilities
Run E2E, API, integration, regression and release tests on voice journeys
Prepare test data and expected outcomes, support business testers during UAT
Run and extend automated suites and evaluation sets
Log defects with clear reproduction steps and transcripts, follow to closure
Flag risks and blockers early
Requirements
Nice to have: Voice testing platforms (Hamming, Cekura, Coval, Botium)
Nice to have: LLM evaluation tools (Promptfoo, DeepEval, LangSmith)
Nice to have: Telephony basics (SIP, Twilio, Azure Communication Services)
Nice to have: ISTQB certification
Nice to have: Responsible‑AI testing (PII, bias, safety)
We are looking for a Data QA Engineer (Middle) for the Data Warehouse & Analytics team to help build a systematic approach to data testing and ensure quality throughout processing stages.
Responsibilities
Побудова та розвиток процесів тестування даних у команді Data Warehouse & Analytics.
Тестування ETL/ELT-процесів та перевірка коректності передачі й трансформації даних із SAP, 1С та інших джерел до Databricks.
Перевірка відповідності даних бізнес-вимогам на всіх етапах обробки: від source-систем до фінальних аналітичних вітрин.
Проведення Data Validation та Source-to-Target Reconciliation для забезпечення точності, повноти й узгодженості даних, перевірка бізнес-логіки трансформацій, правил обробки та збагачення даних.
Виявлення дублів, пропущених записів, некоректних значень та інших аномалій у даних.
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