Python GCP Engineer

• Engineering & Data Pipeline Development:
  • Design, develop, and enhance ETL / data engineering pipelines on GCP
    (BigQuery, DataProc, Cloud Composer)
  • Build and optimize:
    • Data transformations
    • Data ingestion frameworks
    • Pipeline components using Python and PySpark
  • Ensure pipelines are:
    • Scalable
    • Efficient
    • Aligned with best engineering practices

• Quality Engineering & Automation:
  • Design and develop scalable data validation frameworks and automation utilities
  • Implement end-to-end data quality checks, including:
    • Data reconciliation
    • Schema validation
    • Business rule enforcement
  • Build and maintain automated test suites for:
    • Functional testing
    • Regression testing
    • Data validation scenarios

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