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Role Description

This role offers a critical opportunity to ensure the integrity, reliability, and accuracy of enterprise data used across the organization. The Data QA Engineer will focus on validating data pipelines, transformations, analytics outputs, and BI reports, enabling the business to make confident, data-driven decisions. You will design and execute automated tests, implement monitoring frameworks, and perform targeted manual verifications, collaborating closely with Data Engineering and BI teams. The role requires a mix of technical expertise, analytical rigor, and strong problem-solving skills. You will influence data quality standards, improve testing frameworks, and contribute to best practices across projects. This is a remote role, providing flexibility while allowing you to engage in high-impact, mission-critical work.

• Collaborate with engineering and BI teams to translate project requirements into comprehensive data quality test plans and validation criteria.
• Develop, maintain, and execute automated tests for data pipelines, transformations, and analytics outputs, ensuring accuracy and reliability.
• Write and optimize SQL queries for validations, reconciliation, business-rule checks, and regression testing.
• Monitor and manage automated test runs and data observability alerts, ensuring timely detection of anomalies and schema changes.
• Investigate and resolve data issues, tracing data lineage from source to reports, and validate fixes collaboratively with engineers.
• Contribute to the continuous improvement of QA processes, frameworks, monitoring, and documentation of standards.
• Mentor team members and lead high-impact QA initiatives, promoting knowledge sharing and adherence to best practices.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or related field, or equivalent professional experience.
• Minimum of 5+ years of experience in data quality, QA engineering, or a related data-focused role.
• Strong expertise in SQL, Python, and test automation frameworks (e.g., Cypress, Great Expectations).
• Experience with ETL/ELT pipelines, data models, and BI/reporting tools (e.g., Power BI, Tableau).
• Proficiency with CI/CD pipelines, version control (e.g., Git), and Agile development practices.
• Excellent analytical, problem-solving, and attention-to-detail skills.
• Strong communication and collaboration skills to work effectively across cross-functional teams.
• Preferred: Experience with data observability, monitoring, and automated alerting for pipeline health and anomaly detection.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, or related field, or equivalent professional experience.
• Minimum of 5+ years of experience in data quality, QA engineering, or a related data-focused role.
• Strong expertise in SQL, Python, and test automation frameworks (e.g., Cypress, Great Expectations).
• Experience with ETL/ELT pipelines, data models, and BI/reporting tools (e.g., Power BI, Tableau).
• Proficiency with CI/CD pipelines, version control (e.g., Git), and Agile development practices.
• Excellent analytical, problem-solving, and attention-to-detail skills.
• Strong communication and collaboration skills to work effectively across cross-functional teams.
• Preferred: Experience with data observability, monitoring, and automated alerting for pipeline health and anomaly detection.

Benefits

• Competitive salary: $100,000 – $130,000 USD, based on experience and expertise.
• Fully remote work with all required technology provided.
• Comprehensive healthcare benefits, including medical, dental, and vision coverage.
• Paid time off, holidays, and parental leave.
• Professional development opportunities, training, and mentorship programs.
• Collaborative, quality-focused, and dynamic work environment with flexible workflows.
• Opportunities to lead initiatives and influence data quality practices organization-wide.