Automation Test Engineer With BA Skills

Job description:
Role Overview
We are looking for a Business Analyst / Quality Analyst (BA/QA) with experience in business requirement analysis, functional documentation, manual testing, and test automation for cloud-based applications. The role involves understanding business and technical requirements, preparing functional specifications and test scenarios, validating end-to-end workflows, and ensuring the quality, accuracy, and reliability of applications.

The candidate will work on industrial IoT, time-series data, machine learning, real-time analytics, Java/Python/FastAPI services, Azure integrations, and data pipelines. The ideal candidate should be capable of translating business requirements into functional solutions, performing comprehensive manual testing, and supporting automation testing to improve testing efficiency and coverage.

Key Responsibilities
1. Business Analysis
Gather, analyze, and document business, functional, and technical requirements by collaborating with stakeholders, clients and developers.
Prepare Business Requirement Documents (BRDs), Functional Requirement Documents (FRDs), user stories, use cases, process flows, and acceptance criteria.
Conduct requirement discussions and clarification sessions to understand business needs and define expected application behavior.
Analyze existing business processes and identify opportunities for process improvements and enhanced application functionality.
Create and maintain functional documentation, user guides, requirement traceability matrices, and process documentation.
Collaborate with development teams to clarify requirements and ensure alignment between business expectations and technical implementation.
Participate in Agile ceremonies, including sprint planning, backlog refinement, daily stand-ups, sprint reviews, and retrospectives.
Track requirements, tasks, defects, and project progress using Azure DevOps or similar project management tools.
Support user acceptance testing (UAT), client demonstrations, and stakeholder reviews.
2. Quality Assurance – Manual & Automation Testing
Analyze business and functional requirements to prepare test scenarios, test cases, test data, and test execution plans.
Perform manual functional, integration, system, regression, smoke, and end-to-end testing.
Develop, maintain, and execute automated test scripts for selected web applications, APIs, backend services, and critical business workflows.
Perform API testing using Postman, including REST API request/response validation, authentication, status codes, JSON payloads, and negative test scenarios.
Develop and maintain automation scripts using Python, Java, or similar programming languages and frameworks such as Pytest, Selenium, or Playwright.
Validate web applications, backend services, database operations, and integrations between applications and cloud services.
Perform database and data validation using SQL to verify data accuracy, integrity, transformations, and consistency across systems.
Validate time-series, telemetry, sensor, and industrial equipment data, including expected business outcomes.
Test machine learning and analytics features against defined requirements and expected outcomes, where applicable.
Validate data pipelines, ETL processes, Azure integrations, and real-time communication workflows.
Perform manual validation of Power BI dashboards, reports, analytical outputs, and data visualizations.
Automate selected API, regression, integration, and repetitive data validation scenarios to improve testing efficiency and coverage.
Integrate relevant automated test suites into CI/CD pipelines and execute them as part of DevOps processes.
Perform performance, load, and scalability testing using JMeter or similar tools when required.
Identify, document, track, and retest defects; analyze test failures and collaborate with developers to investigate root causes and resolve issues.
Maintain test cases, automation scripts, test data, execution reports, defect records, and test evidence using Azure DevOps or similar tools.
Support UAT, release validation, regression testing, and post-deployment verification.
Explore AI-assisted tools to improve the efficiency of requirement documentation, test case preparation, and selected QA activities, where appropriate.
Required Skills and Qualifications
· Experience in business analysis, requirement gathering, stakeholder communication, and functional documentation.
· Ability to prepare BRDs, FRDs, user stories, use cases, process flows, acceptance criteria, and user guides.
· Understanding of SDLC, Agile/Scrum methodologies, and software development processes.
· Strong knowledge of manual testing concepts, including test case design, test execution, functional, regression, integration, system, smoke, and end-to-end testing.
· Experience in API testing using Postman, REST APIs, JSON, authentication, request/response validation, and negative test scenarios.
· Knowledge of SQL and database testing, preferably with Azure SQL or PostgreSQL, to validate data accuracy, integrity, and transformations.
· Practical exposure to automation frameworks such as Pytest, Selenium, Playwright, or equivalent tools.
· Understanding of API automation, automated regression testing, data validation automation, and end-to-end workflow automation.
· Familiarity with Git, Azure DevOps, CI/CD pipelines, defect tracking, test reporting, and requirement traceability.
· Understanding of cloud-based applications, backend services, APIs, data pipelines, and system integrations.
· Familiarity with Python/FastAPI services, Azure cloud services, and integrations involving databases and data processing.
· Understanding of machine learning concepts and the ability to validate analytics outputs, anomaly detection, forecasting, regression, and predictive maintenance functionality.
· Exposure to time-series data, telemetry, sensor data, IoT, or industrial analytics is preferred.
· Knowledge of performance and load testing using JMeter or similar tools is an advantage.
· Familiarity with WebSockets, real-time communication testing, and Power BI dashboard validation is a plus.
· Exposure to MQTT, OPC UA, Modbus, SCADA, or Industrial IoT is an added advantage.
· Strong analytical, problem-solving, communication, documentation, and debugging skills.
· Ability to collaborate effectively with business stakeholders, developers, QA teams, and data/ML engineering teams.
· Familiarity with AI tools such as ChatGPT, Microsoft Copilot, or similar tools to improve requirement documentation, test case preparation, and productivity.
· Basic understanding of Generative AI, Large Language Models (LLMs), and prompt engineering.
· Exposure to Azure OpenAI, Azure AI services, or other AI platforms.
· Awareness of AI/ML testing concepts and validation of AI-generated outputs.
· Interest in exploring AI-assisted tools to improve business analysis and QA activities.