Data Analytics Lead(ETL Testing & Python Automation) (Karnataka)

Demonstrated expertise in ETL testing, ensuring data accuracy, reliability, and integrity across all stages of data processing. - Strong proficiency in SQL for complex querying, data validation, and troubleshooting. - Solid understanding of data ingestion, transformation, enrichment, quality, governance, lineage, and pipeline design patterns. - Hands-on experience with ETL testing tools such as Data Gaps, QuerySurge, iceDQ, or equivalent platforms. - Proven experience in developing and orchestrating AWS Glue Jobs for ETL workflows. - Skilled in Python for test automation, data validation, and Glue job scripting. - Deep knowledge of Snowflake Data Warehouse and Salesforce Workbench for data management and reconciliation. - Familiarity with cloud platforms (AWS, Azure), particularly in data storage, transformations, and workflow orchestration. - Solid foundation in data modeling principles, including schema design, normalization, and relational structures. - Practical experience in API testing for validating system integrations and data access. - Ability to design, develop, and execute data quality checks and validation frameworks across ETL and reporting layers. - Collaborate effectively with data engineers, analysts, and business stakeholders to define and implement data quality rules and metrics. - Perform source-to-target verification, reconciliation, and anomaly detection to ensure data consistency.Role & responsibilities Build automated validation scripts and integrate data quality tests into CI/CD pipelines. - Investigate, document, and resolve data quality issues, conducting root-cause analysis and preventive actions. - Maintain detailed test plans, mappings, and validation documentation, supporting data governance and metadata management initiatives. Preferred candidate profile .