All fields marked * are required
Job Description
Job Location: Pune/ Noida/Bengaluru/ Gurugram
Work mode: 5 days(2 days WFO )
Total Experience: 4-6yrs
QA Automation Engineer – Data Engineering:
Role Summary:
We are looking for a QA Automation Engineer with strong expertise in Data Engineering validation and automated testing for modern cloud-based data platforms. The role involves validating end-to-end data pipelines built on Medallion Architecture (Bronze, Silver, Gold layers) in Databricks, ensuring data quality, transformation accuracy, scalability, and reliability across batch and near real-time workloads.
The ideal candidate should have experience in automation frameworks, ETL/Data testing, cloud data platforms, and CI/CD integration within enterprise-grade analytics ecosystem.
Key Responsibilities
Data Pipeline Testing:
Validate end-to-end data ingestion, transformation, and consumption pipeline across bronze, silver, and gold layers.
Perform source-to-target data validation for structured.
Validate business rules and data transformations.
Ensure data consistency, completeness, uniqueness and referential integrity.
Automation Testing:
Design and develop automated test frameworks for data validation and regression testing.
Automate ETL and data quality testing using python, SQL, PySpark, or testing frameworks.
Build reusable validation scripts for schema validation, reconciliation, and data drift detection.
Integrate automated test suites into CI/CD pipelines.
Databricks and Cloud Validation:
Validate Databricks notebooks, workflows, Delta Tables and job orchestration.
Test Delta Lake functionalities include ACID compliance, schema evolution and time travel.
Validate performance and scalability of Spark-based transformations.
Required Skills:
SQL
Python
PySpark
Databricks
Batch Pipelines
Incremental Loads
CDC pipelines
Knowledge of Medallion Architecture concepts
Preferred Qualifications:
4-6 Years of experience in QA/Data Testing.
2+ years of experience in Databricks/Data Lakehouse projects.
Experience working in Agile/Scrum delivery models.
Certification in Databricks, Cloud or Testing tool is an advantage.
Required
Preferred
All fields marked * are required
Job Description
Job Location: Pune/ Noida/Bengaluru/ Gurugram
Work mode: 5 days(2 days WFO )
Total Experience: 4-6yrs
QA Automation Engineer – Data Engineering:
Role Summary:
We are looking for a QA Automation Engineer with strong expertise in Data Engineering validation and automated testing for modern cloud-based data platforms. The role involves validating end-to-end data pipelines built on Medallion Architecture (Bronze, Silver, Gold layers) in Databricks, ensuring data quality, transformation accuracy, scalability, and reliability across batch and near real-time workloads.
The ideal candidate should have experience in automation frameworks, ETL/Data testing, cloud data platforms, and CI/CD integration within enterprise-grade analytics ecosystem.
Key Responsibilities
Data Pipeline Testing:
Validate end-to-end data ingestion, transformation, and consumption pipeline across bronze, silver, and gold layers.
Perform source-to-target data validation for structured.
Validate business rules and data transformations.
Ensure data consistency, completeness, uniqueness and referential integrity.
Automation Testing:
Design and develop automated test frameworks for data validation and regression testing.
Automate ETL and data quality testing using python, SQL, PySpark, or testing frameworks.
Build reusable validation scripts for schema validation, reconciliation, and data drift detection.
Integrate automated test suites into CI/CD pipelines.
Databricks and Cloud Validation:
Validate Databricks notebooks, workflows, Delta Tables and job orchestration.
Test Delta Lake functionalities include ACID compliance, schema evolution and time travel.
Validate performance and scalability of Spark-based transformations.
Required Skills:
SQL
Python
PySpark
Databricks
Batch Pipelines
Incremental Loads
CDC pipelines
Knowledge of Medallion Architecture concepts
Preferred Qualifications:
4-6 Years of experience in QA/Data Testing.
2+ years of experience in Databricks/Data Lakehouse projects.
Experience working in Agile/Scrum delivery models.
Certification in Databricks, Cloud or Testing tool is an advantage.
Required
Preferred