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Niche GCP data-quality skillset and lesser-known employer in a non-metro location reduces qualified applicant density.
Core skills (data QA, Python, SQL, cloud) transfer across industries but require data-platform experience.
Multiple mandatory technical skills (Python, GCP, BigQuery, API and performance testing) enforce strict filtering.
Design and execute end-to-end data quality and testing strategies for cloud-based platforms and data pipelines using Python automation.
Validate data accuracy and performance across batch and streaming pipelines, APIs, and multiple database types (PostgreSQL, MongoDB, BigQuery).
Perform performance and load testing; integrate automated validation into CI/CD pipelines; troubleshoot data and pipeline issues collaboratively.
Experience as Data Quality Engineer, SDET, Data Test Engineer, or QA Automation Engineer with modern data platforms.
Strong Python-based test automation and RESTful API testing skills.
Hands-on experience with Google Cloud Platform data technologies (Pub/Sub, GCS, Dataflow, Dataproc, Cloud Composer, BigQuery).
Strong SQL and data validation skills with experience on PostgreSQL/AlloyDB, MongoDB, and BigQuery.
Practical expertise in testing and automating data quality in large-scale cloud-based data environments, especially GCP.
Experience with both batch and streaming data pipelines, including performance and load testing.
Competent in cross-team collaboration to diagnose and resolve complex pipeline and API issues.