What are the responsibilities and job description for the QA Analyst - Data Testing position at Darden?
Job Overview
The Quality Analyst – Data testing is responsible for ensuring the accuracy, completeness, consistency, and reliability of enterprise data across IT enterprise systems. This role partners closely with Data Engineering, BI, Integration, and Product teams to validate data flows to verify that data is accurately transferred and processed across each step of the workflow
ensuring data is analytics ready, trusted, and production safe. This role is expected to be AI enabled, leveraging Gen AI and intelligent tooling to improve testing efficiency, accelerate insights, and enhance data quality practices, while applying strong human judgment and governance awareness.
Key Responsibilites
Data Validation & Integration testing
The Quality Analyst – Data testing is responsible for ensuring the accuracy, completeness, consistency, and reliability of enterprise data across IT enterprise systems. This role partners closely with Data Engineering, BI, Integration, and Product teams to validate data flows to verify that data is accurately transferred and processed across each step of the workflow
ensuring data is analytics ready, trusted, and production safe. This role is expected to be AI enabled, leveraging Gen AI and intelligent tooling to improve testing efficiency, accelerate insights, and enhance data quality practices, while applying strong human judgment and governance awareness.
Key Responsibilites
Data Validation & Integration testing
- Test that data is correctly maintained or transformed as it moves through the IT systems.
- Validate data pipelines to ensure business rule enforcement.
- Perform data accuracy, completeness, and freshness checks supporting dashboards, reports, and analytics use cases.
- Review requirements and build test cases, using SQL queries to check data accuracy.
- Execute integration, system, and regression testing for data pipelines.
- Identify, document, and track data defects to resolution.
- Document and report defects to help identify recurring issues during testing.
- Use Generative AI tools to assist with test design, analysis, documentation, and defect investigation, validating outputs for accuracy and relevance.
- Identify opportunities to leverage automation to improve data testing efficiency and coverage.
- Apply human judgment and oversight when using AI generated outputs to ensure alignment with business rules and data governance standards.
- Contribute to improvements in data testing processes, templates, and repeatable validation patterns.
- 2 years of experience in development or testing
- Skills for data analysis, reconciliation, and validation
- Knowledge of SDLC/STLC and QA best practices
- Strong communication skills with the ability to explain data issues to technical and non technical audiences
- Experience testing BI, reporting, or analytics platforms
- Understanding of data warehousing concepts
- Familiarity with cloud data platforms such as Snowflake, Delta Lake, or similar
- Familiarity with CRM data models and customer data domains
- Experience working in Agile delivery environments
- Exposure to data quality, data observability, or governance practices
- Experience using AI assisted tools in QA, data analysis, or engineering workflows
- Knowledge of restaurant, retail, or consumer data domains
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Analytics, or related field (or equivalent experience)
- Strong analytical and problem solving skills
- Attention to detail and data integrity
- Proactive risk identification and escalation
- Ability to work effectively across cross functional teams
- Collaboration and alignment with automated test practices
- Responsible, pragmatic adopter of AI focused on efficiency and quality