About the Role
We are looking for an experienced Data QA Engineer to drive data validation and automation testing across large-scale data platforms. The ideal candidate will have robust expertise in Python, SQL, PySpark, ETL Testing, Data Validation, and automation frameworks, along with exposure to AI-assisted tools such as GitHub Copilot or Claude. Must-Have Skills
• Strong Python coding and automation skills
• SQL querying, database testing, and stored procedure validation
• PySpark data pipeline validation
• ETL/ELT Testing and Data Quality Validation
• Source-to-Target Data Validation
• Automation-first Regression Testing Frameworks
• Experience using AI-assisted tools (GitHub Copilot, Claude, etc.)
• Data Pipeline Testing and Defect Analysis [Data QA Engineer 1 (1) (004).docx]
Key Responsibilities
• Perform end-to-end data validation across enterprise data platforms.
• Build and maintain automated validation and regression testing frameworks.
• Validate ETL/ELT pipelines, data transformations, and business rules.
• Execute reconciliation, schema, metadata, and lineage validation.
• Develop reusable Python and SQL-based test utilities.
• Identify and investigate data quality issues and anomalies.
• Collaborate with engineering teams to ensure high-quality data delivery.
• Support post-trade and capital markets data validation initiatives. [Data QA Engineer 1 (1) (004).docx] Nice-to-Have Skills
• Azure, Azure Data Factory (ADF), Databricks
• Kafka Testing
• Hadoop / Spark Ecosystem
• NoSQL Databases (MongoDB, Cassandra, DynamoDB)
• Kubernetes
• DevSecOps Tools Please share below details ASAP: Name: Current Company: Current Designation: Current
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📌 Data QA Engineer (India)
🏢 Vertage
📍 India
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