ETL Tester- Bigquery

About this role

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Skills you'll use

What you'll do

• Testing Strategy & Test Design
• Define and maintain testing methodologies for the full GCP data engineering stack: Dataflow (TestPipeline), Dataproc (spark-testing-base or pytest), Cloud Run container tests, and SQL-based data validation in BigQuery/dbt.
• Develop and execute data quality frameworks using dbt tests (schema, singular, freshness) and external tools like Great Expectations, Soda Core, and Dataplex.
• Pipeline & Database Testing
• Implement integration, and regression tests for ETL/ELT pipelines, including container- level and HTTP-triggered tests for Cloud Run.
• Use emulators or dedicated test instances to test Spanner, Cloud SQL, and AlloyDB. Validate stored procedures and database functions with sample data.
• End-to-End (E2E) Pipeline Validation
• Orchestrate comprehensive E2E tests via Cloud Composer/Apache Airflow or scripting. Simulate real-world data flows and validate intermediate and final outputs.
• CI/CD & Automation
• Embed QA in CI/CD pipelines (e.g., GitLab CI, Jenkins, GitHub Actions), automating test execution at all levels including data quality validations and dbt runs.

Who can apply

• Partner with data engineers and stakeholders to review design for testability.
• Mentor junior QA team members, champion QA best practices, and lead efforts to improve data quality KPIs and test effectiveness.
• Utilize Cloud Logging, Monitoring, and observability tools (e.g., Elementary Data) to track pipeline health, test results, and identify anomalies.
• 5+ years in QA or software testing, including focused on data pipelines/data warehouses
• Proficient in complex SQL and writing data validation queries.
• Strong experience with GCP data tools: dbt, BigQuery, Dataflow, Dataproc, Cloud Run, Spanner, AlloyDB, Cloud SQL.
• Hands-on with data-quality frameworks: Great Expectations, Soda Core, dbt-utils, dbt-expectations.
• Familiarity with database emulators and test environment provisioning.

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