Position Overview

We are looking for a skilled QA Python Testing Engineer with strong experience in Python-based testing, Hadoop testing, PySpark/Spark, SQL, and Pandas. The ideal candidate will be responsible for designing and executing test strategies for data-intensive applications, validating large datasets, developing automation frameworks, and ensuring data quality and accuracy across distributed processing environments.

The role requires strong analytical and problem-solving skills, with the ability to work closely with development, data engineering, and business teams to identify and resolve defects.

Key Responsibilities

- Design, develop, and execute functional, regression, integration, and data validation test cases using Python.
- Develop and maintain Python-based test automation scripts and frameworks.
- Perform testing of Hadoop ecosystem components and validate large-scale data processing workflows.
- Validate data processing and transformation logic using PySpark/Spark.
- Perform database and data validation testing using SQL.
- Use Pandas for data manipulation, comparison, validation, and test-data analysis.
- Validate ETL/data pipelines and ensure data accuracy, completeness, consistency, and integrity.
- Perform source-to-target data validation across distributed data platforms.
- Analyze test results, identify defects, and work with development teams to troubleshoot and resolve issues.
- Create and maintain test scenarios, test cases, automation scripts,



and test execution reports.
- Participate in Agile ceremonies including sprint planning, daily stand-ups, reviews, and retrospectives.
- Collaborate with Data Engineers, Developers, Business Analysts, and other QA teams to ensure end-to-end quality.
- Identify opportunities to improve test automation, coverage, and overall QA processes.

Mandatory Skills
- Strong hands-on experience in Python Testing / Python Automation Testing.
- Strong experience in Hadoop Testing and validation of Hadoop-based data processing.
- Hands-on experience with PySpark or Apache Spark.
- Strong proficiency in SQL for data validation and database testing.
- Hands-on experience with Pandas for data analysis and validation.
- Good understanding of ETL/Data Pipeline Testing.
- Strong knowledge of Data Validation, Data Quality, and Reconciliation Testing.
- Experience in developing and executing automated test scripts using Python.
- Solid analytical and debugging skills.

Good to Have
- Experience with Hive, HDFS, Impala, or other Hadoop ecosystem components.
- Experience with Kafka or other data streaming technologies.
- Knowledge of CI/CD and test automation practices.
- Experience working in Agile/Scrum environments.
- Exposure to cloud-based data platforms such as AWS, Azure, or GCP.
- Familiarity with Git and other version-control tools.
- Experience with API testing and REST services.

📌 QA - Python testing (Hyderabad)
🏢 CGI
📍 Hyderabad