Senior Test Automation Engineer

Job summary

Design and maintain scalable automation frameworks while leveraging AI-assisted tools to enhance test coverage and productivity. Perform comprehensive database testing, data migration validation, and integrate automated tests into CI/CD pipelines.

Job details

About the role We are seeking a highly skilled and self-motivated Senior Test Automation Engineer to join our Quality Engineering team. The ideal candidate will have extensive experience in test automation, database validation, AI-assisted testing, and modern quality engineering practices. This role requires expertise in building scalable automation frameworks, validating complex data migrations, and leveraging AI-enabled tools to improve productivity, accelerate testing cycles, enhance test coverage, and continuously improve software quality. The successful candidate will play a key role in driving AI-powered quality engineering practices, championing innovation, and ensuring the effective use of AI technologies while maintaining high standards of quality, security, compliance, and reliability. What you'll do * Design, develop, and maintain scalable automation frameworks using Java, Python, and Playwright. * Develop and execute automated functional, regression, integration, API, and end-to-end test suites. * Perform comprehensive database testing, including data validation, data integrity, data consistency, and backend verification. * Write and optimize complex SQL queries involving joins, subqueries, Common Table Expressions (CTEs), window functions, aggregates, and stored procedures to validate business rules and application data. * Validate database transactions, triggers, stored procedures, views, functions, indexes, and constraints. * Perform end-to-end validation of data across multiple databases and systems to ensure consistency and integrity. * Validate ETL processes and data migration activities, ensuring accurate transformation, reconciliation, and completeness of migrated data. * Perform source-to-target data validation for large-scale migration and integration projects. * Create reusable SQL validation scripts to support automation and regression testing. * Analyze database performance and identify data-related issues impacting application functionality. * Validate data generated through APIs, batch jobs, scheduled processes, and background services. * Perform backend testing by validating application data against business requirements. * Execute performance, load, stress, security, and accessibility testing. * Work with Snowflake to validate data, execute queries, verify data pipelines, and support reporting validation. * Develop reusable automation utilities and testing libraries. * Integrate automated tests into CI/CD pipelines to support continuous integration and continuous delivery. * Utilize AI-assisted tools such as Microsoft Copilot, ChatGPT, Claude, Cursor, GitHub Copilot, and similar technologies to accelerate test design, automation development, defect analysis, SQL generation, troubleshooting, documentation, and productivity improvements. * Leverage Generative AI solutions to create, optimize, and maintain test scenarios, test cases, test data, validation scripts, and quality engineering documentation. * Evaluate, recommend, and adopt emerging AI-enabled testing capabilities that improve efficiency, coverage, risk detection, and release confidence. * Validate and review AI-generated outputs to ensure accuracy, reliability, compliance, and alignment with business requirements. * Contribute to AI testing standards, best practices, governance, and responsible use of AI within the Quality Engineering organization. * Collaborate closely with developers, business analysts, DevOps, product teams, and business stakeholders throughout the software development lifecycle. * Analyze application logs, troubleshoot defects, perform root cause analysis, and continuously improve test coverage. * Create and maintain test strategies, test plans, test cases, automation scripts, SQL validation scripts, and technical documentation. * Mentor junior team members on automation best practices, AI-assisted testing approaches, and quality engineering standards. * Drive continuous improvement initiatives that leverage AI to improve software quality, delivery speed, and operational efficiency. Qualifications * Experience with enterprise applications, microservices, and distributed architectures. * Experience with AWS or Azure cloud platforms. * Experience with test data management and environment management. * Experience working with large datasets and high-volume transactional systems. * Experience leading or supporting AI transformation initiatives within Quality Engineering teams. * Experience establishing AI testing standards, governance practices, and adoption frameworks. * Knowledge of AI-driven testing platforms, intelligent test automation, and predictive quality analytics. * ISTQB or equivalent QA certification. * Self-motivated with the ability to work independently and take ownership of deliverables. * Strong attention to detail and commitment to delivering high-quality software. * Ability to manage multiple priorities in a fast-paced Agile environment. * Passion for continuous learning, emerging technologies, and AI-enabled quality engineering practices. * Strong curiosity and adaptability in evaluating and adopting new AI technologies. * Ability to balance AI-assisted productivity with engineering judgment, critical thinking, and quality standards. * Collaborative mindset with the ability to work effectively in cross-functional teams. * Ability to champion innovation, continuous improvement, and AI adoption across the Quality Engineering organization.

What you’ll do

Design and maintain scalable automation frameworks while leveraging AI-assisted tools to enhance test coverage and productivity. Perform comprehensive database testing, data migration validation, and integrate automated tests into CI/CD pipelines.

Requirements

Requires extensive experience in test automation, database validation, and modern quality engineering practices within enterprise environments. Candidates must possess strong technical skills in Java, Python, and SQL, along with experience in AI-driven testing and cloud platforms like AWS or Azure.

Listed skills

• SQL · Preferred
• CI/CD · Preferred
• Java · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Java
• Python
• Playwright
• SQL
• Snowflake
• Test Automation
• AI-assisted Testing
• Database Validation
• CI/CD
• ETL
• API Testing
• Performance Testing
• Security Testing
• Data Migration
• Generative AI
• Quality Engineering
• Engineering Documentation
• Back End Testing
• Microsoft Copilot
• Playwright (Software Testing)
• GitHub Copilot
• ChatGPT
• Continuous Development
• Environment Management
• Operational Efficiency
• Pipelines
• Generative Artificial Intelligence
• Test Data Management
• Web Accessibility Testing
• Curiosity
• Snowflake (Data Warehouse)
• AI Adoption
• International Software Testing Qualifications Board (ISTQB) Certified
• Emerging Technologies
• AI Testing
• Self-Motivation
• Java (Programming Language)
• Adaptability
• Application Programming Interface (API)
• Agile Methodology
• Artificial Intelligence
• Amazon Web Services
• Systems Engineering
• Automation
• Microsoft Azure
• Reconciliation
• Business Requirements
• Code Coverage
• Hierarchical And Recursive Queries In SQL
• Continuous Improvement Process

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Test Automation Engineer
• Software QA Engineer / Tester
• Software and Applications Developers and Analysts Not Elsewhere Classified
• Software Quality Assurance Analysts and Testers

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