Key Responsibilities

Design, develop, and maintain end-to-end automated regression suites for GTS applications.

Build automation frameworks to validate Spark-based data transformation pipelines.

Validate Airflow DAG orchestration, job dependencies, scheduling, retries, and failure handling.

Develop automated comparison tools for validating outputs generated across AWS and GCP environments.

Implement data quality validation and reconciliation checks using BigQuery, AWS services, XML, JSON, Avro, and Parquet datasets.

Create automated test reporting, trend analysis, and quality dashboards.

Integrate automated testing into CI/CD pipelines.

Support release validation, production readiness testing, and post-release smoke testing.

Collaborate with Development, Product, Data Analysis, and Platform teams to improve test coverage.

Drive continuous improvement in QA processes, automation coverage, and release confidence.

Required Qualifications

Bachelor's degree in Computer Science, Engineering, or related field.





5+ years of QA Automation experience.

Robust hands-on experience with: Java or Python Cucumber/ TestNG/JUnit or equivalent frameworks BDD automation testing Data validation and ETL testing

Experience creating automated regression suites from scratch.

Experience testing Spark jobs and distributed data processing applications.

Strong SQL Skills And Experience Validating Large Datasets.

Hands-on experience with: Apache Airflow Apache Spark Git/GitHub CI/CD pipelines

Experience working in Agile environments.

Preferred Qualifications

Strong Google Cloud Platform (GCP) and AWS experience.

GCP experience with: Dataproc BigQuery Cloud Storage Pub/Sub

AWS experience including: S3 EMR Lambda DynamoDB

Experience with data comparison and reconciliation frameworks.

Exposure to large-scale data migration and cloud migration testing.

Knowledge of XML, JSON, Avro, and Parquet validation.

📌 Associate Engineering Manager (Hyderabad)
🏢 Virtusa
📍 Hyderabad