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Serg K., QA Engineer with QA Automation Engineer, Data Quality

Lviv, Ukraine
Last Updated: 4 Jul 2023
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Language Verified
Programming Skills Verified
CV Verified

- 5 years with QA automation - Strong testing theory understanding. Defect life cycle and issue workflow understanding, Experience in creating and executing test cases. Reporting - Experience with data and BI tools - DevOps experience with CI/CD, pipelines, Docker, AWS, SQL

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QA Automation

QA Automation   5 yr.





Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Mihai Serdean, QA Automation Engineer

Cluj-Napoca, Romania
Last Updated: 15 Sep 2023

Mihai Serdean is a software engineer with 17 years of experience in IT software and QA. He is currently working as a freelancer in software quality assurance and is part of various freelance networks such as Toptal, Upper, Expertlead, and WorkGenius. Mihai has expertise in test automation, performance testing, and using tools such as Selenium WebDriver, Cypress, JMeter, and Postman. He is skilled in multiple programming languages including Java, JavaScript, TypeScript, Python, and .Net. Mihai has a strong background in computer science, holding both a Master's and Bachelor's degree from Universitatea "Babeș-Bolyai" din Cluj-Napoca. He has experience in implementing QA strategies, managing QA teams, and improving QA processes. Mihai has worked with various companies and has a track record of delivering high-quality software solutions.

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QA Automation

QA Automation

Test Automation

Test Automation   17 yr.

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George C., Automation QA Engineer

Bucharest, Romania
Last Updated: 6 Sep 2023
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- QA Automation Engineer with 8+ years proven track record of leading and managing cross-functional teams across a broad spectrum of technical projects - Expertise in team management, defining QA metrics, setting automation standards, and executing test plans - Has 7 years of experience testing Java applications - Has 4+ years working in the banking domain, focusing on delivering robust solutions while consistently improving testing processes. - Has 3+ years of experience conducting automated app testing using Appium on different platforms like Android, iOS - Specialized in Functional Automation (Web, Mobile, Backend) - Experienced in Performance Testing with Locust/JMeter - Upper-Intermediate English

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QA Automation

QA Automation


Java   7 yr.


Appium   3 yr.

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Oleg, Senior Automation QA Engineer

Last Updated: 14 Sep 2023

- Goal-oriented Senior Automation QA Engineer with 8+ years of experience in QA, specializing in manual and automated testing of enterprise-level business and technical solutions. - Strong technical background with proficiency in programming languages such as Java, Kotlin, and Swift. - Extensive experience in functional testing on web and mobile UI, REST API, as well as non-functional testing of web apps. - Skilled in test automation solutions development from scratch, including web UI, REST API, and database levels. - Proficient in performance testing strategies and implementation on web UI and REST API levels. - Experienced in setting up and improving QA standards, processes, and approaches, as well as mentoring and supporting project QA teams. - Strong knowledge of DevOps tools and technologies such as Azure DevOps, Docker, and Jenkins, with experience in integrating test automation into CI/CD pipelines.

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QA Automation

QA Automation


QA   8 yr.

Manual Testing

Manual Testing   8 yr.

Automated testing

Automated testing   8 yr.

Functional Testing

Functional Testing   8 yr.

non-functional testing

non-functional testing   8 yr.

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Maksym P., Automation /Manual QA Engineer

Last Updated: 6 Oct 2023

Senior Automation QA Engineer with over 5 years of experience in the software industry; - Proficient in Atlassian tools (Jira, Confluence, Stash, Bamboo) ; - Skilled in automation testing using Java, Selenium, WebDriver, Selenide, XPath, CSS, JUnit, TestNG, Maven, and Gradle; - Strong background in API and UI automation, with expertise in developing automation frameworks from scratch; - Experienced in continuous integration and deployment using tools like TeamCity and Jenkins; - Knowledgeable in load and performance testing using Apache JMeter; - Experienced in using version control systems like Git; - Familiar with databases like MySQL, Mongo, and ClickHouse.

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QA Automation

QA Automation

Manual QA

Manual QA

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FAQs about QA Automation Development

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If you urgently need a verified and qualified QA Automation developer, and resources for finding the right candidate are lacking, UPSTAFF is exactly the service you need. We approach the selection of QA Automation developers professionally, tailored precisely to your needs. From placing the call to the completion of your task by a qualified developer, only a few days will pass.

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AI tools and expert human reviewers in the vetting process are combined with a track record and historically collected feedback from clients and teammates. On average, we save over 50 hours for client teams in interviewing QA Automation candidates for each job position. We are fueled by a passion for technical expertise, drawn from our deep understanding of the industry.

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Our journey starts with a 30-minute discovery call to explore your project challenges, technical needs, and team diversity. Meet Carefully Matched QA Automation Talents. Within 1-3 days, we’ll share profiles and connect you with the right talents for your project. Schedule a call to meet engineers in person. Validate Your Choice. Bring a new QA Automation developer on board with a trial period to confirm that you’ve hired the right one. There are no termination fees or hidden costs.

How does Upstaff vet remote QA Automation engineers? Arrow

Upstaff Managers conduct an introductory round with potential candidates to assess their soft skills. Additionally, the talent’s hard skills are evaluated through testing or verification by a qualified developer during a technical interview. The Upstaff Staffing Platform stores data on past and present QA Automation candidates. Upstaff managers also assess talent and facilitate rapid work and scalability, offering clients valuable insights into their talent pipeline. Additionally, we have a matching system within the platform that operates in real-time, facilitating efficient pairing of candidates with suitable positions.

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Table of Contents

TOP 15 Tech facts and history of creation and versions about QA Automation Development

  • The concept of QA automation development was introduced in the 1990s as a way to streamline the software testing process by using specialized tools and scripts.
  • One of the early pioneers of QA automation was Boris Beizer, who authored the book “Software Testing Techniques” in 1983, which laid the foundation for many of the methodologies used in automation testing today.
  • In 1999, Kent Beck introduced the concept of “Test-Driven Development” (TDD), which revolutionized the way software was tested by promoting the idea of writing tests before writing the actual code.
  • In 2004, Selenium, an open-source automation testing framework, was released by Jason Huggins. It quickly became one of the most popular tools for web application testing due to its flexibility and robustness.
  • Continuous Integration (CI) became a key practice in QA automation with the introduction of tools like Jenkins in 2011. CI allows for the automatic building and testing of software as changes are made, ensuring early detection of issues.
  • Behavior-Driven Development (BDD) gained popularity in the mid-2000s, with tools like Cucumber and SpecFlow providing a way to define test scenarios in a human-readable format. BDD focuses on collaboration between developers, testers, and business stakeholders.
  • Robot Framework, created by Pekka Klärck in 2005, is a generic automation framework that enables test automation for a wide range of software types. It supports keyword-driven testing and allows for easy integration with other tools.
  • Appium, released in 2012, revolutionized mobile application testing by providing a cross-platform automation framework that supports both Android and iOS devices. It allows for the reuse of code across different platforms.
  • The rise of DevOps in recent years has significantly impacted QA automation. Tools like Docker, Kubernetes, and Ansible have made it easier to build and deploy applications, while also facilitating the automation of testing processes.
  • Artificial Intelligence (AI) and Machine Learning (ML) are being increasingly integrated into QA automation. AI-powered test automation tools can analyze application behavior and generate tests automatically, reducing the effort required to create and maintain test cases.
  • Shift-left testing, a concept introduced in the early 2010s, emphasizes the early involvement of QA in the software development process. By catching and fixing issues earlier, it helps reduce the cost and time associated with bug fixing.
  • Low-code and no-code platforms have emerged as a way to empower business users to create and execute automated tests without the need for extensive programming knowledge. These platforms provide a visual interface for test creation and execution.
  • API testing has become a crucial part of QA automation, with tools like Postman and SOAPUI allowing for the easy creation and execution of API test cases. API testing helps ensure the stability and reliability of the underlying services.
  • Agile methodologies, such as Scrum and Kanban, have become the norm in QA automation development. These methodologies promote iterative development, continuous feedback, and collaboration, resulting in faster delivery of high-quality software.
  • The rise of cloud computing has had a significant impact on QA automation. Cloud-based testing platforms, such as AWS Device Farm and Sauce Labs, provide scalable and cost-effective solutions for testing applications on a wide range of devices and browsers.
  • With the increasing complexity of software systems, test automation frameworks, such as TestNG and JUnit, have evolved to support parallel test execution, data-driven testing, and reporting capabilities, improving the efficiency and effectiveness of QA automation.

Soft skills of a QA Automation Developer

Soft skills are essential for QA Automation Developers as they contribute to effective teamwork, communication, and problem-solving abilities. Here are the key soft skills required at different levels of expertise:


  • Attention to Detail: Paying close attention to details helps in identifying and reporting bugs accurately.
  • Time Management: Managing time efficiently ensures timely completion of tasks and meeting project deadlines.
  • Collaboration: Working well with team members fosters a collaborative environment and enhances productivity.
  • Adaptability: Being adaptable allows junior QA Automation Developers to quickly learn new technologies and adjust to changing project requirements.
  • Effective Communication: Clear and concise communication helps in conveying ideas, issues, and solutions effectively to team members and stakeholders.


  • Critical Thinking: Developing strong critical thinking skills enables mid-level QA Automation Developers to analyze complex problems and find innovative solutions.
  • Leadership: Displaying leadership skills by taking ownership of tasks, providing guidance to junior team members, and leading by example.
  • Problem-solving: Applying logical and analytical thinking to troubleshoot and resolve issues efficiently.
  • Mentoring: Mentoring junior team members by sharing knowledge and providing guidance to help them grow.
  • Conflict Resolution: Effectively resolving conflicts and promoting a positive work environment.
  • Continuous Learning: Demonstrating a willingness to learn new technologies and staying updated with industry trends.
  • Time Management: Efficiently managing time and prioritizing tasks to ensure smooth project execution.


  • Strategic Thinking: Developing a strategic approach to QA Automation by aligning it with overall business goals.
  • Project Management: Demonstrating strong project management skills by overseeing multiple projects, allocating resources effectively, and ensuring timely delivery.
  • Cross-functional Collaboration: Collaborating with other teams, such as development and product management, to ensure seamless integration of QA processes.
  • Quality Advocacy: Advocating for quality standards and driving initiatives to improve overall product quality.
  • Team Management: Managing a team of QA Automation Developers, providing mentorship, and fostering a positive work culture.
  • Client Relationship Management: Building and maintaining strong relationships with clients, understanding their requirements, and ensuring their satisfaction.
  • Decision-making: Making informed decisions based on data analysis and considering the impact on the project and team.
  • Continuous Improvement: Continuously striving for improvement by identifying areas of enhancement and implementing best practices.

Expert/Team Lead

  • Strategic Planning: Developing long-term strategies and roadmaps for QA Automation, aligning them with organizational goals.
  • Technical Leadership: Providing technical leadership to the team, guiding them on complex technical challenges, and promoting knowledge sharing.
  • Innovation: Driving innovation in QA Automation by exploring new tools, frameworks, and methodologies to improve efficiency and effectiveness.
  • Change Management: Managing the transition to new technologies, processes, or methodologies, ensuring smooth adoption across the team.
  • Thought Leadership: Contributing to the QA Automation community through publications, presentations, and participation in industry events.
  • Risk Management: Identifying and mitigating risks associated with QA Automation projects and proactively addressing potential issues.
  • Strategic Partnerships: Collaborating with key stakeholders, such as senior management and clients, to build strategic partnerships and drive business growth.
  • Performance Management: Assessing and managing the performance of team members, providing feedback, and facilitating their professional development.
  • Business Acumen: Understanding the business context and making decisions that align with the organization’s goals and objectives.
  • Continuous Innovation: Encouraging a culture of continuous innovation, experimentation, and learning within the QA Automation team.
  • Communication and Influence: Effectively communicating complex concepts and influencing stakeholders to gain support for QA Automation initiatives.

What are top QA Automation instruments and tools?

  • Selenium: Selenium is an open-source automation testing tool widely used for web application testing. It was first released in 2004 and has gained immense popularity since then. Selenium supports multiple programming languages such as Java, C#, Python, Ruby, etc. It provides a rich set of features for automating browser actions, including form submission, mouse movements, and page navigation. Selenium WebDriver, the most widely used component of Selenium, allows testers to write automated tests that simulate user interactions with the application.
  • Appium: Appium is an open-source mobile application automation testing tool. It was released in 2012 and has become the de facto standard for mobile app testing. Appium allows testers to automate mobile app testing on both Android and iOS platforms using a single codebase. It supports various programming languages such as Java, C#, Python, Ruby, etc. Appium provides a wide range of capabilities, including gesture support, handling multiple devices, and real-time device interaction for both native and hybrid mobile apps.
  • Jenkins: Jenkins is an open-source automation server that facilitates continuous integration and continuous delivery (CI/CD) processes. It was originally developed as Hudson in 2004 but later renamed Jenkins in 2011. Jenkins enables developers and testers to automate the build, test, and deployment processes, ensuring faster and more reliable software delivery. It supports various plugins and integrations with other tools, making it highly customizable and adaptable to different project requirements.
  • JIRA: JIRA is a widely used issue tracking and project management tool developed by Atlassian. Although primarily designed for agile software development, it is also extensively used for managing QA processes. JIRA provides features for creating and tracking bugs, managing test cases, and collaborating with team members. It offers integration with various testing tools, allowing seamless traceability and visibility of testing activities within the development workflow.
  • TestComplete: TestComplete is a commercial automation testing tool developed by SmartBear Software. It provides a comprehensive set of features for functional testing of desktop, web, and mobile applications. TestComplete supports multiple scripting languages, including JavaScript, Python, and VBScript, making it accessible to testers with different programming backgrounds. It offers a robust object recognition engine, built-in test reporting, and integration with popular CI/CD tools.
  • LoadRunner: LoadRunner is a performance testing tool developed by Micro Focus. It has been widely used for load and stress testing of web and mobile applications since its release in 1993. LoadRunner supports a variety of protocols and technologies, allowing testers to simulate realistic user loads and measure system performance under different conditions. It provides detailed performance reports, analysis tools, and integration with other testing and monitoring tools for end-to-end performance testing.
  • Katalon Studio: Katalon Studio is a free automation testing tool for web and mobile application testing. It offers a user-friendly interface and supports both scriptless and script-based test automation. Katalon Studio integrates with popular frameworks like Selenium and Appium, providing a seamless experience for testers. It also offers features for data-driven testing, test case management, and CI/CD integration, making it suitable for both beginners and experienced automation testers.

Cases when QA Automation does not work

  1. Lack of proper test coverage: QA automation may not work effectively if there is insufficient test coverage. If the test cases are not comprehensive enough to cover all the critical functionalities and edge cases, the automation scripts may miss important scenarios, leading to potential issues or bugs in the software.
  2. Dynamic and frequently changing UI: Automation tools rely heavily on the UI elements and their properties to interact with the application. If the user interface is highly dynamic or frequently changes, it becomes challenging to maintain the automation scripts. The automation scripts may fail to locate the elements accurately, leading to test failures and false negatives.
  3. Unstable or unreliable test environment: QA automation requires a stable and reliable test environment to execute the scripts consistently. If the test environment is unstable, with frequent network or system failures, the automation scripts may produce inconsistent results. Flaky test results can undermine the confidence in the automation and make it less reliable.
  4. Complex business logic: Automation scripts are primarily designed to handle repetitive and predictable tasks. However, when dealing with complex business logic or intricate algorithms, automation may not be the most efficient approach. Manual testing with domain expertise might be necessary to ensure the accuracy and correctness of the application’s behavior.
  5. Dependency on external systems: Many software applications rely on external systems or services, such as APIs, databases, or third-party integrations. If the automation scripts heavily depend on these external components, any changes or issues in the external systems can cause the automation to fail. The constant maintenance and synchronization of automation scripts with external dependencies can become time-consuming and prone to errors.
  6. Exploratory testing: Automation is not well-suited for exploratory testing, where the primary goal is to discover new scenarios, uncover hidden defects, or evaluate the user experience. Exploratory testing requires human intuition and creativity, which automation scripts lack. Manual testing is more effective in such scenarios to allow testers to freely explore and validate the software’s behavior.
  7. Cost and time constraints: Implementing QA automation requires significant upfront investment in terms of tools, infrastructure, and skilled resources. In some cases, the cost and time required to develop and maintain automation scripts may outweigh the benefits, particularly for small-scale projects or short-term engagements. Manual testing might be more cost-effective and efficient in such situations.

How and where is QA Automation used?

Case NameCase Description
Regression TestingQA Automation Development is widely used for regression testing, which involves retesting the previously tested functionalities of an application to ensure that any recent changes or updates have not introduced new bugs or issues. By automating this process, QA teams can save time and effort by running automated test scripts that cover a wide range of test scenarios, allowing them to identify any regression issues quickly and efficiently.
Load TestingQA Automation Development is also utilized for load testing, which involves simulating real-world user traffic to test how an application performs under heavy load. By automating the load testing process, QA teams can easily generate and simulate thousands of concurrent users, identifying performance bottlenecks, analyzing system behavior, and ensuring the application can handle the expected load without any performance degradation or crashes.
Data-Driven TestingQA Automation Development is effective in data-driven testing, where multiple test scenarios are executed using different sets of test data. By automating this process, QA teams can easily create and manage test data sets, ensuring comprehensive test coverage by running test scripts with various data inputs. This approach helps identify potential issues related to data handling, boundary values, and system response, improving overall test efficiency and accuracy.
Cross-Browser TestingQA Automation Development is commonly used for cross-browser testing, which involves testing an application’s compatibility and functionality across different web browsers. By automating this process, QA teams can execute test scripts on multiple browsers and versions simultaneously, ensuring consistent behavior and user experience across different platforms. This helps identify browser-specific issues and ensures a seamless experience for end users.
Integration TestingQA Automation Development plays a crucial role in integration testing, which involves testing the interaction between different components or modules of an application to ensure they work together harmoniously. By automating this process, QA teams can simulate various integration scenarios, validate data flow between components, and detect any compatibility issues or communication failures. This helps ensure the smooth integration of different system components and reduces the risk of integration-related defects.

TOP 10 QA Automation Related Technologies

  • Python

    Python is one of the most popular programming languages for QA automation software development. It offers a simple syntax, extensive libraries, and excellent integration capabilities, making it ideal for test automation frameworks like Selenium and Robot Framework.

  • Selenium

    Selenium is a widely used open-source tool for automating web browsers. It supports multiple programming languages, including Python, Java, and C#, and provides a robust set of APIs for interacting with web elements, performing actions, and verifying results, making it a go-to choice for web application testing.

  • Robot Framework

    Robot Framework is a generic open-source test automation framework that uses a keyword-driven approach. It supports both Python and Java, offering a simple and readable syntax for creating test cases and test data. With its extensive library ecosystem and easy extensibility, Robot Framework is widely adopted in QA automation.

  • Java

    Java is a popular programming language for building enterprise-level software, including QA automation frameworks. Its strong object-oriented nature, vast ecosystem of libraries, and platform independence make it a preferred choice for developing robust and scalable automation solutions.

  • JUnit

    JUnit is a unit testing framework for Java that provides a standardized way of writing and executing test cases. It offers annotations, assertions, and test runners, making it easy to create and manage automated tests. JUnit integrates seamlessly with other Java-based automation tools, making it a staple in the QA automation space.

  • Appium

    Appium is an open-source tool for automating mobile applications across different platforms, including iOS and Android. It supports multiple programming languages, such as Java, Python, and Ruby, and provides a unified API for interacting with mobile devices, making it a popular choice for mobile app testing.

  • Postman

    Postman is a widely used API testing tool that simplifies the process of testing and documenting APIs. It offers a user-friendly interface for creating requests, assertions, and test suites, making it easy to automate API testing. With its extensive features and integrations, Postman has become an essential tool for QA automation.

Pros & cons of QA Automation

6 Pros of QA Automation

  • Improved Efficiency: QA automation allows for faster and more efficient testing processes. Automated tests can be executed repeatedly without human intervention, saving time and effort.
  • Increased Test Coverage: With automation, it is possible to test a larger number of scenarios and combinations, increasing the overall test coverage. This helps in identifying more bugs and issues before the software is released.
  • Early Bug Detection: Automated tests can be run early in the development cycle, allowing for early bug detection. This helps in identifying and fixing issues before they become more complex and costly to resolve.
  • Regression Testing: Automation is particularly useful for performing regression testing, which ensures that previously fixed bugs do not reappear in the software. It allows for quick and thorough testing of the entire software system, reducing the risk of regression bugs.
  • Consistency: Automated tests are executed in a consistent manner, eliminating the variations that can occur with manual testing. This ensures that tests are performed the same way every time, leading to more reliable and accurate results.
  • Cost Savings: While there is an initial investment required for setting up and maintaining automation frameworks, in the long run, it can lead to significant cost savings. Automated tests eliminate the need for manual testers to perform repetitive tasks, reducing labor costs.

6 Cons of QA Automation

  • Initial Setup Time: Setting up automation frameworks and creating test scripts can be time-consuming and require specialized skills. This initial setup time should be considered before deciding to automate the testing process.
  • Maintenance Overhead: Automation scripts require ongoing maintenance to keep them up to date with changes in the software. This can be time-consuming and may require regular updates to ensure accurate test results.
  • Complexity: Automation testing can be complex, especially for complex software systems. Testers need to have a solid understanding of automation frameworks and programming languages, which may require additional training and expertise.
  • Limited Scope: Not all types of testing can be effectively automated. Certain testing scenarios, such as usability testing or exploratory testing, may require human intervention and judgment, making automation less suitable.
  • False Positives and Negatives: Automated tests may produce false positives or false negatives, where a test incorrectly passes or fails, leading to incorrect conclusions. Testers need to carefully analyze and validate test results to avoid relying on inaccurate information.
  • Dependency on Tools: QA automation relies on automation tools and frameworks, which may have their limitations. Compatibility issues, tool updates, or changes in the software can impact the effectiveness of automation, requiring adjustments and adaptations.

Hard skills of a QA Automation Developer

Hard skills of a QA Automation Developer:


  • Programming languages: Proficiency in at least one programming language such as Java, Python, or C#.
  • Test automation frameworks: Familiarity with popular automation frameworks like Selenium or Appium.
  • Version control systems: Understanding of version control systems like Git for managing code repositories.
  • Testing methodologies: Knowledge of software testing methodologies such as black-box testing and white-box testing.
  • Test case design: Ability to create effective test cases and test scripts based on functional and non-functional requirements.


  • Continuous integration/continuous delivery (CI/CD): Experience with CI/CD tools like Jenkins or Travis CI to automate build and deployment processes.
  • API testing: Proficiency in testing RESTful APIs using tools like Postman or SoapUI.
  • Database testing: Knowledge of SQL queries and experience in testing database interactions.
  • Performance testing: Understanding of performance testing concepts and experience with tools like JMeter or LoadRunner.
  • Test management tools: Familiarity with test management tools like TestRail or Zephyr for test case management and reporting.
  • Agile methodologies: Experience working in Agile development environments and familiarity with Scrum or Kanban frameworks.
  • Debugging and troubleshooting: Ability to identify and resolve issues by analyzing logs and debugging test failures.


  • Test automation architecture: Proficient in designing and implementing scalable and maintainable test automation frameworks.
  • Code review: Ability to review and provide constructive feedback on code written by team members.
  • Security testing: Knowledge of security testing techniques and experience in identifying vulnerabilities in applications.
  • Load testing: Experience in conducting load and stress testing using tools like Apache JMeter or Gatling.
  • Test data management: Understanding of test data management strategies and techniques.
  • CI/CD pipeline automation: Proficiency in automating CI/CD pipelines using tools like Jenkins or GitLab CI/CD.
  • Containerization: Familiarity with containerization technologies like Docker for creating portable and reproducible environments.
  • Performance tuning: Ability to analyze and optimize test scripts and frameworks for improved performance.

Expert/Team Lead

  • Test strategy and planning: Ability to define test strategies and plans for complex projects.
  • Test environment setup: Experience in setting up and configuring test environments with different combinations of operating systems, browsers, and devices.
  • Test automation leadership: Experience leading a team of automation developers and providing technical guidance.
  • Test framework development: Proficiency in developing custom test frameworks tailored to specific project requirements.
  • Code refactoring: Ability to refactor and optimize existing automation code for improved maintainability and efficiency.
  • Test automation metrics and reporting: Experience in defining and tracking automation metrics to measure the effectiveness of test automation efforts.
  • Test automation best practices: Knowledge of industry best practices for test automation and ability to mentor team members.
  • Test automation tool evaluation: Experience in evaluating and selecting the right automation tools and technologies for projects.
  • Collaboration and communication: Strong collaboration and communication skills to work effectively with cross-functional teams.
  • Leadership and mentoring: Ability to lead and mentor junior team members, providing guidance and support.
  • Continuous learning: Demonstrated commitment to staying updated with the latest trends and advancements in QA automation.

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