QA DATA Engineer - Remote

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Job Overview

The QA Data Engineer at NTT DATA North America will play a crucial role in ensuring the integrity, accuracy, and reliability of data used in various applications. The candidate will work collaboratively with cross-functional teams to design, implement, and maintain quality assurance practices for data systems. This role demands a proactive approach to identifying areas of improvement within data processes and a commitment to leveraging best practices in data quality management.

Job Responsibilities

• Develop and execute detailed test plans, test cases, and test scripts for data quality assurance.
• Monitor data flow systems and data pipelines to ensure data integrity and consistency.
• Analyze, validate, and document data quality issues and improvement opportunities.
• Collaborate with data engineers and other stakeholders to develop strategies for data quality enhancements.
• Utilize automated testing tools to increase efficiency and effectiveness of testing processes.
• Perform regression and performance testing to validate data processing systems.
• Participate in data governance initiatives to align data practices with organizational standards.
• Provide training and support to team members on QA methodologies and tools.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 3+ years of experience in data quality assurance or QA engineering.
• Proficiency in SQL and experience with databases such as MySQL, PostgreSQL, or Oracle.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is advantageous.
• Experience with automated testing tools and frameworks (e.g., Selenium, Apache JMeter).
• Strong analytical and problem-solving skills with a keen attention to detail.
• Excellent communication and interpersonal skills.

Technologies & Tools

The QA Data Engineer will work with a variety of technologies and tools to enhance data quality and performance. Key technologies include SQL for database querying, ETL tools for data integration, automated testing frameworks such as Selenium, and various data visualization platforms to monitor data health and quality. Familiarity with cloud environments (AWS, Azure) is also beneficial as part of modern data infrastructure.

Ideal Candidates

Ideal candidates for the QA Data Engineer position are those who possess a robust analytical mindset, a strong attention to detail, and a commitment to quality. They demonstrate the ability to work independently while being collaborative team players, effectively communicating findings to both technical and non-technical stakeholders. A proactive approach towards problem-solving, alongside a passion for continuous learning and improvement in data quality practices, marks an exemplary candidate for this role.