Work extensively with the GCP ecosystem, including Pub/Sub, Google Cloud Storage (GCS), Dataflow, Dataproc, Cloud Composer, and BigQuery.
Perform database validation using PostgreSQL/AlloyDB, MongoDB, and BigQuery.
Troubleshoot data discrepancies, pipeline failures, API issues, and performance bottlenecks.
Build automated data reconciliation and validation checks to identify missing, duplicate, inconsistent, incorrect, or delayed data.
Collaborate with Data Engineering, Development, DevOps, and Product teams to investigate and resolve data-quality issues.
Integrate automated data, API, and application quality checks into CI/CD pipelines.
Support data profiling, governance, cataloging, lineage, and automated data-quality controls.
Contribute to continuous improvement of data-quality frameworks, automation, testing standards, and processes.
Document test scenarios, validation results, defects, root causes, and resolutions.
Qualifications
Required
Proven experience as a Data Quality Engineer, Data Test Engineer, SDET, QA Automation Engineer, or similar role.
Strong hands-on experience with Python-based test automation.
Strong experience testing RESTful APIs and backend services.
Hands-on experience with Playwright or Cypress.
Strong experience with GCP data technologies, particularly Pub/Sub, GCS, Dataflow, Dataproc, Cloud Composer, and BigQuery.
Strong SQL and data-validation skills with experience working with large and complex datasets.
Experience with PostgreSQL/AlloyDB, MongoDB, and BigQuery.
Hands-on experience with performance/load testing, preferably using k6 or similar tools.
Strong understanding of ETL/ELT, batch and streaming pipelines, data reconciliation, schema validation, data integrity, and data-quality principles.
Strong analytical, debugging, problem-solving, and communication skills.
Preferred
Experience with ClickHouse or other high-performance columnar databases.
Experience with Dataplex for data profiling, cataloging, governance, and automated data-quality controls.
Experience integrating automated testing into CI/CD pipelines.
Knowledge of data observability, data lineage, metadata management, and cloud-native monitoring.
Experience working in the automotive, automotive technology, dealership, or transportation
