QA (ETL + Selenium)

3 weeks ago

India Cozzera Full time
Job Title: Data Engineer QA (ETL + Selenium)

Location: Remote (1–2 days/month in-office at HCL - Noida, Bangalore, Pune, Chennai, Hyderabad, Gurgaon, or Indore)

Shift Timing: 11:00 AM – 8:30 PM IST

Experience: 5+ Years

Background Verification: Mandatory

Job Summary:

We are seeking a highly skilled and detail-oriented Data QA Engineer with expertise in ETL testing and Selenium automation. The ideal candidate will be responsible for ensuring the accuracy, integrity, and quality of data pipelines by designing and executing test strategies that cover both functional and automated testing. This position offers the flexibility of remote work with minimal in-office requirements.

Key Responsibilities:

- Design, develop, and execute ETL test frameworks for validating complex data pipelines and transformation processes.
- Perform detailed data validation, functional, and regression testing on data workflows and integrations.
- Develop and maintain automated test scripts using Selenium with Java or Python.
- Reconcile and validate data between source and target systems to ensure accuracy and consistency.
- Collaborate with Data Engineers, Analysts, QA Leads, and Developers to support data quality and governance efforts.
- Maintain comprehensive documentation including test plans, test cases, and test execution results.
- Participate in Agile ceremonies and contribute to continuous improvement of QA processes.

Required Skills:

- 5+ years of professional experience in QA with a focus on ETL/Data Testing.
- Strong knowledge of ETL testing methodologies, transformation logic, and data validation techniques.
- Hands-on experience with Selenium automation tools using Java or Python.
- Proficient in writing complex SQL queries for data validation and profiling.
- Familiar with Agile/Scrum environments and tools like JIRA for defect tracking.
- Excellent analytical and troubleshooting skills.
- Strong verbal and written communication and documentation abilities.

Nice to Have:

- Experience with cloud data platforms like Azure, AWS, or GCP.
- Familiarity with data warehouses such as Snowflake, Amazon Redshift, or Google BigQuery.
- Exposure to CI/CD pipelines and automated test execution tools

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