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Operations & Project Management
Data Test Engineer
Fynbosys IncAustin, TX🇺🇸United StatesPosted 10 Jul 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
Hi
Role : Data Test Engineer
Location : Austin, TX (Hybrid)
Design and maintain Python-based e2e test automation workflows and frameworks for ETL pipelines, APIs, and data systems
Leverage AWS services including Athena, Glue, Lambda, RDS, S3, and QuickSight for data validation, analysis, and reporting
Expand Automation for NSCC, BETA, Atria(TAMP/IPA), DBMF and the CFN Sandbox validation.
Write advanced SQL queries to validate datasets and support reporting needs
Execute and manage automated tests via GitHub Actions (GHA) within CI/CD pipelines
Develop and execute API automation using Playwright to validate service reliability and integrations
Capture and publish test results to dashboards, enabling visibility into data quality and system health
AI experience is a must - Use AI-assisted tools such as Copilot and Cursor to improve development efficiency and code quality
Collaborate with cross-functional teams to ensure scalable, maintainable, and high-quality data testing practices
Location : Austin, TX (Hybrid)
Design and maintain Python-based e2e test automation workflows and frameworks for ETL pipelines, APIs, and data systems
Leverage AWS services including Athena, Glue, Lambda, RDS, S3, and QuickSight for data validation, analysis, and reporting
Expand Automation for NSCC, BETA, Atria(TAMP/IPA), DBMF and the CFN Sandbox validation.
Write advanced SQL queries to validate datasets and support reporting needs
Execute and manage automated tests via GitHub Actions (GHA) within CI/CD pipelines
Develop and execute API automation using Playwright to validate service reliability and integrations
Capture and publish test results to dashboards, enabling visibility into data quality and system health
AI experience is a must - Use AI-assisted tools such as Copilot and Cursor to improve development efficiency and code quality
Collaborate with cross-functional teams to ensure scalable, maintainable, and high-quality data testing practices
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