Software QA Engineer

Artech
San Diego, CA, United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$93,600 - $104,000
Working hours
Regular working hours

Tech stack

Testing (Software) Automation of Tests Batch Processing Data Validation Data Integrity Software Debugging Hardware Design Python (Programming Language) Log Analysis Regression Analysis E2e Testing Systems Integration
+5 more
Data Processing Scripting Bug Reporting Data Management Data Pipelines

Requirements

Software Testing, Testing, Python Programming/Scripting Language, Test Automation, Analysis Skills, Hardware-Software Integration, Data Management, Debugging Skills, Data Quality, Software Testing, Our client in San Diego seeks a Test Engineer with 2+ years of manual and automated testing, strong Python scripting, hardware/software integration, E2E testing, exploratory testing, log analysis, debugging, data pipelines, and data validation experience., * 2+ years of professional experience in hands-on manual and automated testing across software and/or hardware integration, with proven skill in designing and executing end-to-end test plans.

  • Strong hands-on testing intuition: Experience conducting exploratory, ad-hoc, and user-scenario testing directly on devices and test benches to surface subtle edge cases that automated tests miss.
  • 2+ years of coding and debugging experience in Python, with an emphasis on test automation, tooling, or data processing.
  • Demonstrated debugging & root-cause analysis skills: Skilled at parsing system logs, triaging regressions, and driving complex issues to resolution cross-functionally.
  • Experience with data pipelines and automation: Familiarity with building, maintaining, or validating automated workflows, test harnesses, or batch processing pipelines.
  • Exposure to data collection and curation: Experience executing data collection protocols, verifying data integrity, and curating technical/sensor datasets.
  • High autonomy and precision: Self-starter capable of managing competing priorities independently, with meticulous attention to detail and data integrity.
  • Strong communication skills: Ability to clearly document reproduction steps, triage findings, and present quality risks to engineering stakeholders.

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