Data QA Engineer

Vertage; Pune District; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Vertage Inc. in Pune, India seeks an experienced Data QA Engineer to drive data validation and automation testing across large-scale data platforms. You will leverage Python, SQL, PySpark, and ETL testing to ensure data quality and reliability across pipelines.

We expect expertise in data validation, regression frameworks, and AI-assisted tooling such as GitHub Copilot and Claude, with a strong bias for automation and defect analysis. Knowledge of capital markets data is a plus.

Qualifications

• Proficient Python coding for data validation and automation.
• Expertise in SQL querying, DB testing and stored procedures.
• ETL/ELT testing and data quality validation.
• Source-to-target data validation across pipelines.
• Automation-first regression testing frameworks.
• Experience with AI-assisted tools (GitHub Copilot, Claude).
• Experience with data pipeline testing and defect analysis.

Responsibilities

• Build and maintain automated validation and regression testing frameworks.
• Validate ETL/ELT pipelines, 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.
• Strong in Capital Markets or Banking domain expertise.

Skills

Python coding

SQL querying

ETL Testing

Data Validation

Automation testing frameworks

AI-assisted tools

Source-to-Target Data Validation

Data Pipeline Testing

PySpark

Kafka Testing

Hadoop / Spark Ecosystem

GitHub Copilot

Claude

Tools

GitHub Copilot

Claude

Job description

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 strong 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
• 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

• 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.
• Strong in Capital Markets or Banking domain expertise.

Nice-to-Have Skills

• Kafka Testing
• Hadoop / Spark Ecosystem