Data Quality Analyst Job at Yaddala Consulting in Alpharetta

*** This position is a Contract-to-Hire role, open to visa-independent candidates***

Data Validation and Testing:

• Design and execute test plans, cases, and scripts to validate data pipelines, business intelligence (BI) reports, dashboards, ETL processes, schemas, tables, stored procedures, queries, and jobs for both on-premises and cloud-based data environments.
• Perform thorough data quality assessments, focusing on completeness, accuracy, consistency, and timeliness.
• Identify, document, and track data defects, collaborating with data engineers (ETL developers) to resolve issues efficiently.
• 4-6 years of experience leading and conducting Data Quality Assurance (QA) testing, including hands-on experience with manual and automated testing, test data generation, and validating Data Lakes, Data Warehouse models (e.g., Star Schemas), ETL processes, tables, views, cubes, reports, dashboards, and integrations for inbound and outbound data flows and inter-connected systems.

Automation and Continuous Integration:

• Develop automated test scripts using tools such as Python, SQL, or cloud-native testing frameworks.
• Integrate automated testing into CI/CD pipelines, enabling continuous testing and real-time monitoring of data quality.
• Maintain and improve the automation framework to ensure scalability and adaptability to evolving data requirements.

Reporting and Analytics:

• Generate detailed reports on data quality metrics, test coverage, and defect rates, providing actionable insights to support ongoing improvements.
• Create dashboards and visualizations to track trends in data quality over time.

Technical Skills:

• 5+ years of experience with complex SQL, Python, or other scripting languages for data testing and test automation.
• Hands-on experience with cloud-based data services, including Azure DevOps, Azure Blob Storage, Azure Data Factory, and Cloud Power.
• Familiarity with CI/CD tools like Jenkins, GitLab, etc., and integrating automated testing into deployment pipelines.
• In-depth knowledge of data quality frameworks and tools.