Description

You will test AI-based data augmentation processes, perform ETL testing, and validate metadata quality across data pipelines.

This role is on-site.

Responsibilities

• Test AI-based data augmentation pipelines against accuracy and quality benchmarks.
• Conduct ETL testing, validating data extraction, transformation, and loading across data pipelines.
• Validate metadata, schema alignment, and data integrity across multiple data sources.
• Create detailed test plans, cases, and scripts for AI and ETL components.
• Identify, document, and report defects, collaborating with engineering and data science teams.

Required Skills

• 4–6 years of experience in software testing, specifically in AI/ML testing and ETL/data pipeline validation.
• Strong knowledge of ETL Tools and SQL.
• Proficiency in metadata validation and data quality checks for large datasets.
• Familiarity with testing frameworks like PyTest.
• Experience with API testing using Postman.
• Experience with defect tracking using JIRA.
• Proficiency in Python.
• Strong analytical skills and attention to detail.
• Ability to join immediately.

Key Skills

Education

Any Graduate