Automation Engineer Jobs

About The Position

Requirements

• 4–7 years of experience in QA Automation
• Strong hands-on experience with Postman/Newman (API) and at least one UI framework: Selenium, Robot, Playwright or Cypress
• Solid Python scripting skills for automation, JSON handling, and building data quality validation scripts
• Experience with CI/CD integration (Jenkins, GitHub Actions) for both API and UI test pipelines
• Familiarity with page object models, cross-browser testing, JSON diff libraries, and data-driven test approaches
• Proficient SQL skills (joins, subqueries, window functions, CTEs, aggregations) for data analysis and validation
• Experience validating source-to-target mappings, ETL outputs, transformation logic, and business rule compliance
• Understanding of data quality dimensions: accuracy, completeness, consistency, timeliness, validity, and uniqueness
• Ability to perform cross-system data reconciliation (source vs. target, API vs. database) and schema validation
• Familiarity with data governance, audit requirements, and compliance standards for financial data
• Experience using AI coding assistants (GitHub Copilot, Cursor, Codeium) for writing and refactoring test code
• Hands-on familiarity with LLM-based tools (ChatGPT, Claude, Gemini) for test case generation, debugging, data analysis, and documentation
• Ability to craft effective AI prompts for test scripts, SQL queries, and validation logic; awareness of AI limitations and critical review of AI outputs
• Strong attention to detail with a data accuracy mindset; analytical thinking to investigate complex discrepancies
• Excellent communication, documentation habits, and ability to collaborate in a distributed team
• Curious, proactive learner comfortable with ambiguity and evolving specifications

Nice To Haves

• Experience with a cloud data platform (Databricks, Snowflake, Redshift, BigQuery) is a plus
• Familiarity with Databricks notebooks or Lakehouse concepts
• Exposure to data validation frameworks (Great Expectations, Deequ, Soda) or data observability tools (Monte Carlo, Bigeye)
• Experience working with DevOps pipelines — Jenkins, GitHub
• Knowledge of automation frameworks, especially Robot Framework with Selenium/Playwright
• Exposure in working and leading AI initiatives
• Ability to reason statistically about datasets — detecting outliers, sampling strategies, and validating metric correctness
• Experience testing financial/banking data APIs
• Experience with AI-powered test platforms (Testim, Mabl, Katalon AI, Applitools) or building custom AI agents for test workflows
• Visual regression testing and accessibility testing (WCAG) for data-driven web applications

Responsibilities

• Build, maintain, and execute automated API validation suites using Postman/Newman and Python across multiple environments and datasets
• Design, develop, and maintain UI automation frameworks using Selenium or Playwright to validate data-driven web applications, dashboards, and reports
• Develop end-to-end automated test suites validating full data flow from backend data pipelines and APIs to front-end UI visualizations
• Ensure data rendered in UI components accurately matches underlying data sources and business logic
• Contribute to scalable and reusable automation frameworks with configuration-driven API coverage and maintainable Page Object Models
• Leverage AI coding assistants (e.g., GitHub Copilot, Claude) to accelerate test development and auto-generate test cases from OpenAPI/Swagger specifications and UI requirements
• Apply AI-powered visual testing and self-healing locator capabilities to detect UI regressions and reduce test maintenance effort
• Design and execute comprehensive data quality validation across platforms, including source-to-target mappings, transformation logic, and business rule enforcement
• Perform SQL-based data analysis in Databricks to validate completeness, accuracy, null handling, referential integrity, duplication, and aggregation correctness
• Validate schema evolution, data freshness, and cross-system reconciliation across upstream sources, data lake/warehouse, and downstream APIs
• Develop and maintain Python-based data quality frameworks, validation libraries, and automation pipelines
• Capture, version, and compare API responses across test runs using JSON baseline comparisons
• Ensure adherence to data governance, audit, and control requirements, with strong focus on financial and regulated datasets
• Use AI/ML-driven data profiling to detect anomalies, distribution shifts, and pattern deviations
• Identify, analyze, and report data quality and automation failures, performing root cause analysis in collaboration with engineering and data teams
• Build and maintain quality dashboards using Power BI, Databricks SQL, or Python to track historical trends and validation outcomes
• Define, monitor, and report data quality KPIs including accuracy, completeness, timeliness, consistency, and validity
• Use AI-based summarization tools to auto-generate execution reports, defect summaries, and quality trend insights, including predictive indicators where applicable
• Collaborate closely with Data Scientists, Engineers, Product Managers, and stakeholders to define data requirements and quality expectations
• Participate actively in Agile ceremonies and contribute to sprint planning, execution, and retrospectives
• Document test strategies, automation coverage, validation workflows, and API contracts in Confluence
• Leverage AI assistants for test planning, coverage gap analysis, risk-based prioritization, and consistent documentation maintenance

Benefits

• Competitive benefits, including a range of Financial, Health and Lifestyle benefits to choose from
• Flexible working options, including home working, flexible hours and part time options, depending on the role requirements
• Unlimited PTO policy, floating holidays, volunteering days and a day off for your birthday
• Learning and development tools to assist with your career development
• Work with industry leading Subject Matter Experts and specialist products
• Regular social events and networking opportunities
• Collaborative, supportive culture, including an active DE&I program
• Employee Assistance Program which provides expert third-party advice on wellbeing, relationships, legal and financial matters, as well as access to counselling services