GCP Data Quality Test Engineer – Retail Domain
Job Description:
• Partner with Data Engineers, Analysts, and business stakeholders to define quality requirements.
• Document test cases, data validation rules, and best practices for scalable data governance.
• Develop and implement test cases for ETL/ELT pipelines, data transformation, and ingestion processes.
• Perform data validation, execute test cases (manual or automated) and analyze results. Regression testing ensures sufficient error validation is present. Reconcile variances and data anomalies to ensure high-quality data.
• Validate data transformations and ingestion processes for structured and unstructured data.
• Monitor and troubleshoot data issues, failures, and inconsistencies across the pipeline.
• Provide support for root cause analysis and resolution of data-related defects, including the identification of code changes.
• Document and track defects, providing detailed reports to development teams for resolution.
• Participate in the design and implementation of automated testing scripts to improve testing efficiency.
• Conduct regression testing to ensure that new code changes do not adversely affect existing functionality.
• Perform post-release and post-implementation validation of software performance in production environments.
• Continuously monitor and evaluate the quality of software deliverables, providing feedback for improvement opportunities.
• Collaborate with end users to gather feedback.
Requirements:
• 3-5+ years of experience in data engineering, data testing, or quality assurance.
• Strong proficiency in advanced SQL, and data validation frameworks. (test strategies).
• Familiarity with GCP data services (BigQuery, Dataflow, Dataproc, Cloud Storage) and Python.
• Familiarity with automated testing frameworks for data (e.g., Great Expectations, dbt tests).
• Able to be hands-on with data and create test cases for stated requirements.
• Experience working with and integrating Retail Data.
Benefits:
• Partner with Data Engineers, Analysts, and business stakeholders to define quality requirements.
• Document test cases, data validation rules, and best practices for scalable data governance.
• Develop and implement test cases for ETL/ELT pipelines, data transformation, and ingestion processes.
• Perform data validation, execute test cases (manual or automated) and analyze results. Regression testing ensures sufficient error validation is present. Reconcile variances and data anomalies to ensure high-quality data.
• Validate data transformations and ingestion processes for structured and unstructured data.
• Monitor and troubleshoot data issues, failures, and inconsistencies across the pipeline.
• Provide support for root cause analysis and resolution of data-related defects, including the identification of code changes.
• Document and track defects, providing detailed reports to development teams for resolution.
• Participate in the design and implementation of automated testing scripts to improve testing efficiency.
• Conduct regression testing to ensure that new code changes do not adversely affect existing functionality.
• Perform post-release and post-implementation validation of software performance in production environments.
• Continuously monitor and evaluate the quality of software deliverables, providing feedback for improvement opportunities.
• Collaborate with end users to gather feedback.
Requirements:
• 3-5+ years of experience in data engineering, data testing, or quality assurance.
• Strong proficiency in advanced SQL, and data validation frameworks. (test strategies).
• Familiarity with GCP data services (BigQuery, Dataflow, Dataproc, Cloud Storage) and Python.
• Familiarity with automated testing frameworks for data (e.g., Great Expectations, dbt tests).
• Able to be hands-on with data and create test cases for stated requirements.
• Experience working with and integrating Retail Data.
Benefits: