Description

Validate ETL/ELT pipelines and AI/ML models to ensure data quality, correctness, and production reliability.

This role is on-site.

Responsibilities

• Validate ETL/ELT pipelines from source to target, ensuring data governance and compliance standards.
• Perform data quality checks for completeness, accuracy, and consistency across large datasets.
• Design, execute, and automate test cases using SQL and Python, implementing CI/CD testing for data pipelines.
• Conduct data reconciliation and aggregation validation for data lakes and warehouses.
• Validate AI/ML models, including training data quality, model correctness, and production reliability.

Required Skills

• 10+ years of experience in data testing and quality assurance.
• Strong proficiency in SQL and Python for test automation.
• Hands-on experience with data warehouses: Snowflake, Redshift, BigQuery, or Azure Synapse.
• Understanding of AI/ML concepts, including ML algorithms (Regression, Classification, Clustering) and evaluation metrics.
• Knowledge of feature engineering and training vs. inference pipelines.
• Experience collaborating with data engineers, analysts, and business teams.
• Bachelor's degree in Computer Science or related field.

Key Skills

Education

Bachelor's degree