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.
- Robust 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

📌 Data Analytics Lead(ETL Testing & Python Automation) (Bengaluru)
🏢 PwC
📍 Bengaluru