Quality Assurance Engineer III

Why Pearson?

At Pearson, you’ll join a mission-driven team dedicated to helping people make progress in their lives through learning. We value curiosity, collaboration, and innovation—empowering every employee to make a real impact. If you’re passionate about education and growth, Pearson is the place to thrive.

Job Summary

We are looking for a skilled Data Quality / ETL Test Engineer (Individual Contributor) to support data integration, analytics, and reporting initiatives. The ideal candidate will have a strong foundation in ETL concepts, database and SQL skills, data analysis, and testing, with hands‑on experience in Google Cloud Platform (GCP) and BigQuery. This role involves close collaboration with data engineers, business analysts, and stakeholders to ensure high‑quality and reliable data solutions.

Key Responsibilities

• Execute ETL and data warehouse testing for data pipelines and analytics solutions.
• Perform data analysis, reconciliation, and validation testing across source and target systems.
• Write and execute complex SQL queries to validate data transformations based on business rules.
• Prepare and maintain test strategies, test plans, test cases, and related QA documentation.
• Validate data for accuracy, completeness, consistency, and timeliness.
• Identify, log, and track defects, and actively participate in defect triage discussions with development and data engineering teams.
• Develop and maintain Python automation scripts for repetitive data validation and regression testing.
• Execute data validation and testing on Google Cloud Platform, with a strong focus on BigQuery datasets.
• Understand business requirements and translate them into effective data test scenarios.
• Communicate test progress, defects, and data quality risks clearly to stakeholders and project teams.
• Support UAT, production validations, and post‑release data verification when required.

Required Skills & Qualifications

Technical Skills

• Strong understanding of ETL processes, data warehousing concepts, and relational databases.
• Experience in data analysis and data testing within analytics or reporting environments.
• Proficiency in writing complex SQL queries for data validation and troubleshooting.
• Hands‑on experience with Google Cloud Platform (GCP) and BigQuery.
• Working knowledge of Python for test automation and data validation.
• Experience using defect tracking tools (e.g., JIRA or similar).

Testing & Documentation

• Experience creating test strategies, test cases, test scenarios, and supporting documents.
• Good understanding of data quality checks and ETL testing types such as source‑to‑target, transformation, and reconciliation testing.
• Ability to validate business rules and logic through structured testing approaches.

Communication & Collaboration

• Strong written and verbal communication skills.
• Ability to interact regularly with stakeholders to clarify requirements and provide quality updates.
• Good analytical, problem‑solving, and attention‑to‑detail skills.
• Ability to work independently as an individual contributor within a collaborative team environment.

Good to Have

• Exposure to Agile/Scrum delivery models.
• Experience with data orchestration or modeling tools (e.g., dbt, Airflow).
• Familiarity with CI/CD concepts for data or test automation.
• Experience working in enterprise‑scale data platforms or cloud environments.

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