Data QA Engineer

Project description

The ETL/Data QA Engineer will be responsible for ensuring the accuracy, reliability, and quality of data processed through the organisation's data warehousing and integration platforms. Operating within established testing and governance frameworks, the engineer will validate ETL processes, conduct detailed source-to-target data verification, and contribute to continuous improvements in data quality practices. This role demands strong hands-on experience with Informatica PowerCenter, SQL, Python, and AI-driven automation, as well as the ability to collaborate effectively with cross-functional teams.

Responsibilities

• - Validate ETL mappings, workflows, and transformations to ensure compliance with business and technical requirements. - Perform source-to-target validation by conducting SQL-based data checks to verify completeness, accuracy, and data integrity. - Execute ETL test cycles, including data-quality checks for both full and incremental data loads. - Lead defect triage sessions, facilitating timely resolution and communication among development, business, and QA teams. - Utilize Informatica PowerCenter for ETL validation, debugging, and workflow monitoring. - Apply ETL and data-warehousing concepts, demonstrating a strong understanding of principles, architecture, and best practices. - Use Unix/Linux commands for job monitoring, log analysis, and operational support. - Leverage Python and AI expertise to support automation, data validation, and advanced testing scenarios. - Analyze and document test data, results, and recommendations to aid decision-making. - Support integrated testing by creating and maintaining test data, training data, and automated scripts. - Drive continuous improvement by reviewing testing processes and recommending enhancements.

SKILLS

Must have

• Bachelor's Degree in IT, Business, Computer Science, or a related field
• Software Quality Assurance professional with 5 to 8 years' experience
• Informatica PowerCenter expertise with strong ETL validation and troubleshooting capability
• Extensive experience with ETL concepts & technologies, Data migration testing, Data warehouse testing, and BI Reporting
• Extensive experience in data automation using Python
• High level of Proficiency in writing complex SQL queries in Azure Databricks from Business requirements to read data from source DB hosted in Azure and compare it with the target DB
• Proficiency in relational database models, SQL queries, XML data models
• Extensive experience with software test automation tools and working in fast-paced Agile environments
• Good knowledge of testing lifecycle processes
• Experience with Atlassian tools (Jira and Confluence) and integrating them into automation testing frameworks
• Good communication and presentation skills
• Experience in Waterfall and Agile environments

Nice to have

Experience in the finance industry is highly desirable.