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Quality Assurance Engineer III
Pearson VUEData Quality/ETL Test Engineer focusing on data integration and analytics at Pearson in Chennai. Collaborating with engineers and analysts to ensure data quality and reliability in solutions.
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
ETLdata warehousingSQLdata analysisdata validationPythontest automationdata quality checksdefect trackingreconciliation testing
Soft Skills
communicationcollaborationproblem-solvingattention to detailstakeholder management
Tools & Technologies
Google Cloud PlatformBigQueryJIRA
Industry Keywords
data pipelinesanalytics solutionstest strategiestest plansUATproduction validations
Tech Stack
Tools & technologiesBigQueryCloudETLGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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).
- 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.
Benefits
Comp & perks- Health insurance
- Flexible work arrangements
- Professional development