About Us
SCB DataX is the data and AI company of the SCBX (SET: SCB.BK) group. Our mission is to provide the group's companies the technology, tools, and insights to drive their growth, efficiencies, and customer experiences.
Our leading-edge, cloud-native data platform and AI products enable secure data exchange and cross-pollination of insights, as well as external data enrichment from our data partners.
Our research and development teams are building the next-generation solutions for sharing data and intelligence across the group companies, with the aim to become ASEAN's most admired AI-led company, making material contribution to AI in our region.
We are proud of being awarded the Thai Board of Investment (BOI) promotion for the development of our state-of-the-art digital platform, and the recognition of our contribution to the Thai economy and tech community.
About Teams & Roles:
As a Quality Assurance Engineer, you will ensure high-quality AI-driven data solutions and microservices. You will work closely with data engineers, data scientists, and developers, integrating testing into the agile software development lifecycle.
This role requires technical expertise in microservices, containerized environments (Docker), automation frameworks, and AI model testing. As a QA representative in the Scrum team, you will maintain quality throughout the project lifecycle by actively participating in test planning, execution, and continuous improvement.
Your Responsibility
You will be responsible for designing and developing a comprehensive QA program, which includes creating automated testing strategies and utilizing appropriate tools to ensure efficiency and coverage. You will design and execute usability tests, thoroughly documenting and reporting your findings to the design team. Interaction with clients may be required to understand their product requirements thoroughly.
- Own the QA role in the project by ensuring high standards of data quality, automation coverage, and microservice reliability.
- Collaborate with data engineers, data scientists, and developers to implement test strategies for microservices and AI models.
- Develop and execute comprehensive test plans, test cases/scenarios, and test automation for applications built on microservices, including API and data pipeline testing.
- Understand AI model testing, including feature engineering, label engineering, and model validation.
- Participate in design reviews, providing input on requirements, product design, and potential issues.
- Ensure test planning, execution, and reporting maintain high quality and consistency.
- Track project status, report risks, and proactively anticipate and mitigate potential issues.
- Analyze test results, identifying performance bottlenecks, AI model inconsistencies, microservice defects, and usability concerns.
- Drive test automation by designing robust test scripts for microservices, APIs, and data pipelines.
- Guide and facilitate QA processes within the Scrum team, ensuring that testing activities align with sprint goals.
- Enforce quality control, proactively identifying risks, verifying requirements, and promoting test best practices.
- Generate reports on test execution status, defects, and automation results, while tracking quality metrics.
Qualifications
- Bachelor's degree in computer science, software engineering, or other related fields
- Minimum 3 years of Quality Assurance engineering or similar role with extensive experience in automation frameworks and microservices testing.
- Proven experience developing and implementing QA plans.
- Up-to-date knowledge of software test design and testing methodologies.
- Proficiency in automation tools (e.g., Pytest, Testify, JUnit, Postman, Selenium, Cypress, or Playwright).
- Proficiency in at least one programming language (e.g., Go,Python, Java, JavaScript – NodeJS, AngularJS, TypeScript).
- Strong experience with SQL, NoSQL, and data validation in big data environments.
- Experience in API and microservice testing. Knowing RESTful and GraphQL services is plus.
- Proficiency with Docker, Kubernetes, and containerized testing strategies.
- Strong understanding of CI/CD, DevOps, and test automation in cloud-native architectures.
- Proficiency with Git for version control.
- Knowledge of Vector DB and AI-related development is a plus.
- Ability to guide and support QA activities within an Agile/Scrum team, ensuring comprehensive test coverage.
- Strong analytical skills, problem-solving abilities, and excellent communication.
