Exp - 8+ yrs
Role - permanent
Notice - 30 days
Locals and expats residing in Malaysia only.
Senior Test Automation Engineer
Key Responsibilities
Automation of Data Processing & Visualization Testing: Develop and maintain automated test scripts for validating
the functionality, performance, and accuracy of data processing pipelines, analytics algorithms, and visualization
dashboards.
Data Pipeline & Engine Testing: Ensure the entire data pipeline, from ingestion to analysis to visualization, is
thoroughly tested for reliability and integrity.
Performance Testing: Conduct load and performance testing to validate that the data analytics engine can handle
large datasets and high volumes of data requests in real-time.
End-to-End Testing: Implement comprehensive end-to-end test automation covering all phases of the data
lifecycle, including preprocessing, analysis, visualization, and report generation.
Collaboration with Development Teams: Work closely with data engineers, architects, and developers to define
test strategies, integrate test automation into CI/CD pipelines, and ensure high test coverage for analytics features.
Innovation in Testing Tools: Research and integrate new test automation tools and methodologies to improve the
quality and efficiency of data testing.
Continuous Improvement: Drive continuous improvements in the testing process to increase test accuracy, reduce
test cycle time, and improve test automation coverage for the data analytics system.
Required Qualifications
Experience: 8+ years of experience in software testing, with significant experience automating testing for data
intensive applications.
Programming Skills: Proficiency in programming languages like Python, Java, or JavaScript for writing test scripts
and automating test cases.
Automation Tools: Hands-on experience with test automation frameworks such as Selenium, Cypress, or similar
tools for UI and data-driven testing.
Data Expertise: In-depth understanding of data processing, ETL pipelines, and analytics engines. Experience with
SQL and NoSQL databases for validating data integrity.
Visualization Testing: Strong knowledge of data visualization tools such as Power BI, Tableau, or D3.js and their
specific testing requirements.
Performance Testing: Experience with performance testing tools (e.g., JMeter, LoadRunner) for data processing
and analytics engines.
Agile & CI/CD: Familiarity with Agile development and continuous integration/continuous delivery (CI/CD)
processes, ensuring automated tests are part of the software delivery pipeline.
Collaboration: Strong communication skills and ability to work in a cross-functional team to align on test strategies
and objectives.
Preferred Qualifications
Real-Time Data Testing: Experience testing real-time data processing systems and ensuring low-latency, high
performance analytics pipelines.
Cloud Platforms: Familiarity with cloud-based environments (AWS, GCP, Azure) for deploying and testing data
analytics applications.
Machine Learning Models: Knowledge of testing workflows involving AI/ML models, including data pre-processing,
feature engineering, and model validation.
Security Testing: Experience with security testing in the context of data analytics, ensuring privacy and protection
of sensitive data.
DevOps Practices: Experience integrating automated tests into DevOps pipelines for seamless deployment and
testing.
