About the role
Responsibilities:
- Perform ETL testing, data reconciliation, and end-to-end data validation.
- Validate data movement across source systems, ETL processes, Kafka streams, and target databases.
- Develop and maintain test automation scripts using Python.
- Test and monitor Kafka producers, consumers, topics, and message flows.
- Perform SQL-based data verification and database testing.
- Integrate test automation into CI/CD pipelines and Agile delivery processes.
- Utilize AI-assisted testing tools and generative AI for test case generation, test data creation, defect analysis, and test optimization.
- Collaborate with developers, data engineers, and business stakeholders to ensure data quality and reliability.
Requirements:
- 5+ years of experience in ETL testing and data validation.
- Strong hands-on experience with Python, SQL, and Kafka.
- Expertise in testing data warehouses, ETL pipelines, and large datasets.
- Experience with automation frameworks and scripting.
- Knowledge of REST API testing and CI/CD tools (Jenkins, Git, Azure DevOps, etc. ).
- Familiarity with Agile and DevOps methodologies.
- Exposure to AI-powered testing tools, Microsoft Copilot, GitHub Copilot, or similar AI solutions.
Preferred Skills:
- Finance / Banking / Wealth Management domain experience preferred.
- Experience with data migration, data warehousing, and cloud data platforms.
- Knowledge of AI/ML concepts for test optimization and predictive quality analytics.
Professional Attributes:
- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder management abilities.
- Ability to work independently and within cross-functional teams.
- Proactive mindset with a focus on quality and continuous improvement.