Data Quality Analyst

Role Overview

The Data Quality Analyst role based in Austin, TX (and Charlotte, NC) centers on designing and maintaining automated testing workflows and frameworks primarily leveraging Python. This position focuses on end-to-end test automation specifically for ETL pipelines, APIs, and data systems to ensure robust data quality standards.

Key Duties

• Create and upkeep Python-driven automation frameworks covering ETL processes, API endpoints, and other data platforms.
• Utilize various AWS services including Athena, Glue, Lambda, RDS, S3, and QuickSight to perform data validation, comprehensive analysis, and reporting functions.
• Expand automation efforts to cover multiple platforms such as NSCC, BETA, Atria (TAMP/IPA), DBMF, and the CFN Sandbox for thorough validation.
• Construct complex SQL queries to validate datasets and support reporting requirements.
• Manage and run automated test suites integrated with GitHub Actions within continuous integration and delivery pipelines.
• Develop API automation tests using Playwright to verify service dependability and integration quality.
• Collect and disseminate test results through dashboards to provide clear visibility into data quality and operational health of systems.
• Apply AI tools like Copilot and Cursor actively to enhance coding efficiency and improve code quality.
• Work collaboratively across teams to build scalable and maintainable data testing strategies that uphold quality standards.