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.
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