Key Responsibilities :

- Design, develop, and maintain automated test frameworks and scripts using Python.

- Validate complex ETL workflows, data pipelines, and data transformation processes.

- Develop and execute automated data validation and reconciliation tests using PySpark and SQL.

- Perform end-to-end testing of data ingestion, processing, and reporting systems.

- Execute functional, integration, regression, and automation test suites across applications and data platforms.

- Perform API testing and service validation to ensure reliability and data integrity.

- Validate large datasets and perform backend testing using advanced SQL queries.

- Collaborate with developers, data engineers, business analysts, and QA teams to ensure quality delivery.

- Analyse test results, identify defects, and support root cause analysis of data and application issues.

- Support test execution within Agile/Scrum environments and contribute to sprint planning, estimation, and retrospectives.

- Work with cloud-hosted applications and data platforms on AWS.

- Contribute to automation strategy, framework enhancements, and continuous quality improvement initiatives.

Skills & Qualifications :

- 5 to 8 years of overall experience in Software Testing and Quality Assurance.

- Strong hands-on experience in Python Automation Testing.

- Solid experience working with PySpark for data validation, testing, and large-scale data processing.

- Strong understanding of ETL testing concepts, data warehousing, and data pipeline validation.

- Advanced SQL skills with experience in complex queries, data validation, reconciliation, and troubleshooting.

- Experience in designing and maintaining automation frameworks.

- Good understanding of API Testing and service validation.

- Exposure to AWS Cloud environments.

- Strong experience working in Agile/Scrum delivery models.

- Strong analytical, troubleshooting, and problem-solving skills.

- Excellent communication and collaboration abilities.