Apex Systems
Quality Analyst
Apex Systems - Richmond, Virginia, United States, 23220
Work at Apex Systems
Overview
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Overview
QA Analyst
Data & ML Focus
Contract: 12+ months, continuous extensions Location: Richmond, VA or Dallas, TX
flexible to work more remote after the first couple months. Initially 2-3 days per week onsite. Job Summary We are seeking a QA Analyst to support an ML platform, focusing on full-stack and data-centric applications. This role bridges automation, data engineering, and machine learning (ML) operations, ensuring robust testing of production-grade applications and data pipelines. The ideal candidate will be technically proficient, business-savvy, and capable of working across teams to validate data integrity and application functionality. Key Responsibilities Lead and execute QA testing across full-stack and data/ML applications. Translate business and functional requirements into test cases and validation strategies. Perform manual and automated testing, including ETL and source-to-target data validation. Collaborate with data engineers, data scientists, and QA teams to ensure quality across the SDLC. Validate SQL queries and Python scripts to ensure data accuracy and business logic alignment. Support QA efforts for applications transitioning from development to production. Recommend and implement appropriate testing tools and frameworks. Required Skills & Tools SQL (Advanced)
Strong ability to write and validate complex queries. Python (Intermediate)
Comfortable reading, understanding, and modifying scripts. PostgreSQL
Experience with stored procedures, triggers, and data validation. Snowflake
Familiarity with querying and validating data in Snowflake. Testing Tools (Preferred Experience) QTest NeoLoad Tosca Katalon Selenium HP UFT (Unified Functional Testing) Preferred Qualifications 23 years of QA experience in a production environment. Experience in data-centric QA roles (not just front-end testing). Familiarity with ML workflows and data pipelines. Ability to work independently and communicate effectively with technical and business stakeholders. Quick learner with a proactive mindset. EEO Employer
Data & ML Focus
Contract: 12+ months, continuous extensions Location: Richmond, VA or Dallas, TX
flexible to work more remote after the first couple months. Initially 2-3 days per week onsite. Job Summary We are seeking a QA Analyst to support an ML platform, focusing on full-stack and data-centric applications. This role bridges automation, data engineering, and machine learning (ML) operations, ensuring robust testing of production-grade applications and data pipelines. The ideal candidate will be technically proficient, business-savvy, and capable of working across teams to validate data integrity and application functionality. Key Responsibilities Lead and execute QA testing across full-stack and data/ML applications. Translate business and functional requirements into test cases and validation strategies. Perform manual and automated testing, including ETL and source-to-target data validation. Collaborate with data engineers, data scientists, and QA teams to ensure quality across the SDLC. Validate SQL queries and Python scripts to ensure data accuracy and business logic alignment. Support QA efforts for applications transitioning from development to production. Recommend and implement appropriate testing tools and frameworks. Required Skills & Tools SQL (Advanced)
Strong ability to write and validate complex queries. Python (Intermediate)
Comfortable reading, understanding, and modifying scripts. PostgreSQL
Experience with stored procedures, triggers, and data validation. Snowflake
Familiarity with querying and validating data in Snowflake. Testing Tools (Preferred Experience) QTest NeoLoad Tosca Katalon Selenium HP UFT (Unified Functional Testing) Preferred Qualifications 23 years of QA experience in a production environment. Experience in data-centric QA roles (not just front-end testing). Familiarity with ML workflows and data pipelines. Ability to work independently and communicate effectively with technical and business stakeholders. Quick learner with a proactive mindset. EEO Employer