Data Analyst QA Lead
Centstone
Location: Remote
Job Type: Contract
Experience: Senior-level experience in data analysis and QA Position Overview
We are seeking an experienced Data Analyst QA Lead to support data-driven applications and workflows. This role combines data analysis, quality assurance, data validation, SQL/PL/SQL development, Python scripting, and QA leadership.
Responsibilities-
Lead QA activities for data-centric applications, platforms, and workflows.
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Analyze requirements and develop data validation strategies and test scenarios.
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Perform data analysis and validation using SQL and PL/SQL .
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Use Python for data analysis, test scripting, validation, and automation.
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Perform ETL, data pipeline, functional, integration, regression, and system testing.
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Identify data discrepancies, perform root-cause analysis, and coordinate defect resolution.
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Develop test plans, test cases, test data, QA documentation, and test reports.
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Validate applications and data within AWS cloud environments .
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Collaborate with developers, data engineers, business analysts, and stakeholders.
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Lead defect triage, tracking, and resolution activities.
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Support QA automation, data quality initiatives, and process improvements.
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Provide technical guidance to QA team members as needed.
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Strong experience in Data Analysis and Quality Assurance .
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Hands-on experience with AWS and cloud-based data environments.
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Strong Python programming and scripting skills.
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Advanced SQL and PL/SQL skills.
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Experience with database, ETL, and data pipeline testing.
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Strong understanding of QA methodologies, SDLC, and testing processes.
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Experience developing test plans, test cases, and test scenarios.
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Strong defect management, troubleshooting, and root-cause analysis skills.
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Excellent analytical, communication, and stakeholder management skills.
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Fully remote opportunity.
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Combination of data analysis and QA leadership responsibilities.
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Work with AWS and cloud-based data environments.
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Strong focus on SQL, PL/SQL, Python, and data validation.
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Opportunity to support QA automation and data quality initiatives.
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