About Client :
Our client is a French multinational information technology (IT) services and consulting company, headquartered in Paris, France.
Founded in 1967, It has been a leader in business transformation for over 50 years, leveraging technology to address a wide range of business needs, from strategy and design to managing operations.
The company is committed to unleashing human energy through technology for an inclusive and sustainable future, helping organisations accelerate their transition to a digital and sustainable world.
They provide a variety of services, including consulting, technology, professional, and outsourcing Details :
Location : Pan India.
Mode Of Work : Hybrid.
Notice Period : Immediate Joiners.
Experience : 6- 8 Description Responsibilities :
- Design, develop, and maintain automated test scripts using Python and Pytest for data pipelines and platforms.
- Implement system, integration, and performance testing strategies for data workflows.
- Collaborate with data engineers and DevOps teams to integrate testing into CI / CD pipelines using Azure DevOps.
- Validate data transformations and integrity using SQL queries and automated checks.
- Build reusable testing frameworks and utilities for scalable data validation.
- Monitor and report on test coverage, test results, and quality metrics.
- Troubleshoot and debug test failures and data issues in Databricks Skills & Qualifications :
- 3+ years of experience in automation testing with a focus on data systems.
- Proficiency in Python and SQL for scripting and data validation.
- Hands-on experience with Pytest for test automation.
- Familiarity with Databricks and Azure DevOps (code repositories, pipelines).
- Strong understanding of data engineering workflows, data quality, and testing best practices.
- Experience with CI / CD pipelines and version control systems (e.g., Git).
- Excellent problem-solving skills and attention to Qualifications :
- Experience with data validation tools or frameworks (e.g., Great Expectations).
- Knowledge of cloud data platforms (Azure, AWS, or GCP).
- Exposure to performance testing tools and techniques for large-scale data systems.
(ref : hirist.tech)