Junior QA Specialist - USC / GC

🌍 Remote, USA 🎯 Full-time πŸ• Posted Recently

Job Description

Title: QA Specialist Location: 100% Remote Mode: Contract Client: Mitchell Martin / Capital One Preferred Visa: USC & GC Only Mandatory Skills: Test Engineer with AWS, Azure, Snowflake, Databrick, Airflow, Exploratory testing, Integration Testing. Job Description: Role Overview The Solution QA team will focus on exploratory, production-oriented testing across complex data engineering integrations-specifically Snowflake, Databricks, and Slingshot software extensions. This is not a UAT/automation/regression testing role. It's designed to think like a customer, uncover integration issues in production-like environments, and collaborate closely with engineering, product, and support teams. Key Responsibilities β€’ Test in production-like environments to surface issues tied to integrations and extensions within Snowflake and Databricks β€’ Identify and reproduce bugs related to: API failures, Orchestration gaps, Misconfigurations β€’ Validate customer-critical workflows using Airflow, Terraform, DBT, ADF, and relevant data engineering tooling β€’ Assist in reconfiguring environments across AWS and Azure β€’ Communicate findings clearly with engineering, product, and support team β€’ Support upcoming platform changes as Slingshot begins incorporating AI-driven features Experience β€’ 3+ years in QA (must match tools/expectations in JD) β€’ Strong data engineering fundamentals β€’ Hands-on cloud experience: AWS + Azure (both required) β€’ Testing background: β€’ Exploratory testing β€’ Integration testing β€’ Experience with common QA tools (no automation required) Technical Skills β€’ Snowflake β€’ Databricks β€’ APIs (debugging, failure analysis, configuration) β€’ Airflow (familiarity) β€’ Terraform (familiarity) β€’ DBT (familiarity) β€’ Azure Data Factory (familiarity) Additional Notes β€’ Not customer-facing; all interactions are internal β€’ Part of Support under Go-to-Market; manager's background includes Release Engineering β€’ Works with 10-15 product engineering teams β€’ Automation may be encouraged but not required β€’ Team acts as the "customer environment," so multi-cloud knowledge is essential β€’ Can onboard ASAP Apply tot his job

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