Excellent Opportunity For ETL Testers with Python

We are looking for an experienced ETL Test Engineer with strong expertise in data warehouse testing, ETL validation, Oracle SQL and Python-based test automation. The candidate should have experience validating complex data pipelines, transformations and large-volume datasets. Exposure to AI/GenAI-based testing, data-quality validation or intelligent test automation is desirable.

Key Responsibilities

• Perform end-to-end testing of ETL pipelines and data warehouse solutions.
• Validate data extraction, transformation and loading across source and target systems.
• Develop complex Oracle SQL and PL/SQL queries for data validation and reconciliation.
• Verify source-to-target mappings, transformation rules and business logic.
• Perform data completeness, accuracy, integrity, consistency and duplicate checks.
• Validate incremental loads, full loads, historical loads and change-data-capture processes.
• Test stored procedures, functions, packages, views and database jobs.
• Develop reusable Python scripts and automation frameworks for ETL and database testing.
• Automate data comparison, reconciliation, regression testing and quality checks using Python.
• Perform high-volume data validation and identify performance bottlenecks.
• Validate job scheduling, dependency handling, error handling, restartability and recovery processes.
• Conduct functional, integration, regression, system and performance testing.
• Analyse failed ETL jobs and perform root-cause analysis in collaboration with developers and data engineers.
• Create test strategies, test plans, test cases, traceability matrices and defect reports.
• Track defects and coordinate with development, business and data teams until closure.
• Participate in Agile ceremonies and communicate testing status, risks and dependencies to stakeholders.
• Explore AI/GenAI tools for test-case generation, SQL generation, data profiling, anomaly detection and defect analysis.

Mandatory Skills

• Strong experience in ETL testing and data warehouse testing.
• Strong hands-on experience with Oracle SQL and PL/SQL.
• Ability to write complex SQL queries involving joins, subqueries, CTEs, analytical functions and aggregations.
• Experience validating source-to-target mappings and transformation rules.
• Strong knowledge of data reconciliation, data validation and data-quality testing.
• Hands-on Python scripting experience for test automation.
• Experience testing batch-processing and data-integration workflows.
• Good understanding of dimensional modelling, fact tables, dimension tables and Star/Snowflake schemas.
• Experience with defect-management and test-management tools.
• Strong analytical, debugging and problem-solving skills.
• Good stakeholder communication and documentation skills.