QA Engineer

Primary responsibilities:

• Test and validate ETL pipelines and data workflows, ensuring accuracy and consistency from data ingestion to visualization.
• Collaborate with developers, product managers, and other stakeholders in an Agile environment, adhering to Scrum principles.
• Design, develop, and execute manual and automated test cases to ensure the quality of data engineering and visualization solutions.
• Verify the functionality, performance, and security of data systems using tools and frameworks relevant to Spark, Kafka, and StarRocks.
• Identify, document, and track bugs and issues using appropriate tools, working with the team to resolve them efficiently.
• Contribute to the development and maintenance of test plans, strategies, and scripts for tools like Power BI and Data Warehousing.
• Continuously learn and explore tools and technologies like MinIO, Kerberos, and Iceberg to enhance QA processes.

Required Qualifications:

• 2-4 years of experience in QA engineering with exposure to testing data pipelines or data engineering projects.
• Strong knowledge of manual and automated testing methodologies, tools, and processes.
• Familiarity with ETL testing, data validation, and SQL for verifying data integrity and transformations.
• Basic understanding of tools and technologies like Spark, Kafka, and Power BI.
• Exposure to Agile methodologies and Scrum principles.
• Attention to detail with strong analytical and problem-solving skills.
• Good communication skills and ability to work collaboratively in a team environment.

Preferred Qualifications:

• Experience testing visualization tools like Power BI and validating dashboards.
• Familiarity with data security and governance concepts, including tools like Kerberos.
• Prior experience with test automation tools for data pipelines.