Job Requirements

We are looking for a detail-oriented QA Engineer – Data Engineering to ensure the quality, accuracy, completeness, and reliability of data pipelines, ETL/ELT workflows, data lakes, and data warehouse solutions.

The candidate will be responsible for validating data ingestion, transformation logic, source-to-target reconciliation, schema changes, and data processing workflows. The ideal candidate will have solid hands-on experience with SQL, Python, data validation, ETL testing, and automated data quality frameworks. Familiarity with AWS data services, distributed data processing, and pipeline observability is highly desirable

Analyze data engineering requirements and develop comprehensive test plans, test scenarios, and test cases.

Validate end-to-end data pipelines, including ingestion, transformation, processing, and loading.





Perform source-to-target data reconciliation to verify record counts, field mappings, and transformation accuracy.

Develop automated data validation scripts using Python and SQL.

Test ETL/ELT workflows for data completeness, accuracy, consistency, uniqueness, and integrity.

Validate structured and semi-structured datasets, including CSV, JSON, XML, and Parquet.

Test data transformations, aggregations, joins, filtering logic, and business rules.

Identify duplicate records, missing values, invalid data, schema mismatches, and unexpected data changes.

Data pipeline validation, E2E testing automation, data quality checks, observability validation

Work Experience

5-7Years

📌 Lead Software Engineer (Bengaluru)
🏢 Virtusa
📍 Bengaluru