Data Quality & ETL Analyst AI- Pipelines

Job Summary

This role is responsible for ensuring the accuracy, reliability, and quality of enterprise ETL pipelines and AI-ready datasets. The individual will support analytics, business intelligence, and AI/ML initiatives by validating data pipelines, improving data quality frameworks, and enabling trustworthy model inputs.

• Lead ETL and data quality testing initiatives across multiple data platforms
• Validate data pipelines supporting AI/ML models and analytics dashboards
• Implement AI-assisted testing techniques (anomaly detection, rule discovery)
• Develop reusable SQL/Python-based frameworks for automated data validation
• Review training datasets for consistency, completeness, and data integrity
• Identify and resolve data quality issues across batch and incremental loads
• Partner with data engineers and AI teams to ensure reliability of model inputs
• Ensure adherence to data governance, QA standards, and best practices
• Support Agile delivery through CI/CD-aligned data testing processes

• 6–10 years in ETL/Data Warehouse testing and data quality engineering
• Strong SQL expertise (joins, aggregations, subqueries)
• Solid understanding of data warehousing concepts (fact/dimension models, star schema)
• Hands‑on experience in ETL testing tools (Informatica, Talend, Data Stage, ADF, etc.)
• Experience with databases such as Oracle, SQL Server, Snowflake, Teradata, PostgreSQL
• Exposure to AI/ML data pipelines and feature engineering validation
• Familiarity with data observability or AI‑enabled QA tools
• Working knowledge of Agile and CI/CD practices

• Experience with cloud platforms (AWS, Azure, GCP, Snowflake)
• Basic Python or shell scripting for data validation
• Exposure to BI tools (Power BI, Tableau) validation
• Experience in Agile/Scrum environments

• Bachelor’s degree in Computer Science, IT, Engineering, or equivalent

Net App is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification.