Quality Assurance Data Engineer

Quality Assurance Data Engineer

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We are seeking a Quality Assurance Data Engineer to play a crucial role in ensuring the integrity, reliability, and high performance of our decision‑making data platform. Your expertise will be pivotal in enforcing data quality standards, performing rigorous testing, detecting and resolving data issues, and supporting the continuous improvement of our software development processes. With strong analytical and communication skills, this role brings attention to detail and technical expertise to the testing process, ensuring the delivery of robust and error‑free data analytical solutions.

This role involves both manual and automated testing, contributing to the overall success of the development lifecycle.

• Bachelor’s degree in Computer Science, Information Technology, or a related field
• Experience performing integrated application quality assurance and project management
• Extensive experience with developing and testing front‑end applications
• Strong analytical and problem‑solving ability
• Familiarity with automation testing tools and processes (Tricentis Tosca)
• Experience working with Microsoft Azure services, including Data Bricks
• Strong understanding of Python, SQL
• Proficient in Jira and Zephyr Scale
• Familiarity with Agile development methodologies and participation in Agile teams
• Knowledge of Machine Learning Operations (MLOps) principles and practices
• Excellent problem‑solving skills and attention to detail
• Strong communication and teamwork skills to collaborate effectively with various stakeholders

• Develop and execute comprehensive test plans based on project requirements and specifications
• Create and maintain detailed testing documentation including test cases, test scripts, and test results
• Execute functional, regression, and performance testing to identify and resolve issues
• Collaborate with data engineers and developers to maintain high standards of data quality and consistency
• Identify, log, and track defects in the systems, working with cross‑functional teams to resolve them in a timely manner
• Participate in Agile/Scrum ceremonies, contributing to the continuous enhancement of data processes and data platform
• Advocate for best practices in QA and contribute to the development of automated testing strategies
• Uphold standards of data integrity and contribute to continuous improvement initiatives within the QA process
• Ensure quality and reliability of machine learning pipelines, including data preprocessing, model training, and deployment workflows
• Monitor and validate ML model performance in production environments, ensuring compliance with MLOps best practices
• Collaborate with ML engineers and data scientists to implement automated testing and CI/CD for ML models

• Medical insurance
• Vision insurance
• 401(k)

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