QA Engineer

• Technical Issue Identification & Root Cause Analysis: Identify, investigate, and triage technical issues within the data engineering tech stack (specifically focusing on [Specify Key Technologies - e.g., Python, SQL, Airflow, dbt]). Conduct thorough root cause analysis, utilizing logs, database queries, and system monitoring data to pinpoint the source of problems.
• Log Analysis & Monitoring: Monitor and analyze system logs (e.g., using CloudWatch to validate application functionality, identify performance bottlenecks, and proactively detect anomalies. Develop and maintain dashboards to visualize key system metrics.
• Database Querying & Analysis: Utilize SQL to query and analyze data within the Snowflake data warehouse. Develop and execute complex queries to investigate data discrepancies, identify trends, and support troubleshooting efforts. Familiarity with SQLAlchemy is a plus.
• AWS Service Support: Collaborate with the engineering team on the support and monitoring of AWS services utilized within data engineering (g., EC2, S3). Assist with troubleshooting issues related to these services.
• Collaboration & Requirements Translation: Collaborate with Product Managers and engineers to understand business requirements and translate them into actionable test requirements and test plans. Participate in sprint planning and daily stand-ups.
• QA Execution: Conduct thorough QA tasks, including ticket review, refinement, testing (manual and potentially exploratory), and bug identification.
• Scrum Team Support: Partner with the scrum team to manage backlogs, refine tickets, and support roadmap development.
• UAT Support: Assist with UAT testing, stakeholder communication, and documentation to align team efforts with business goals.
• Compliance & Reporting: Ensure adherence to company policies, including timely reporting of noncompliance.
• Code of Conduct: Responsible for adherence to the Capital Rx Code of Conduct including reporting of noncompliance.

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