Data Quality Engineer-Azure Data Platform Testing
At a glance
Mid-level Data Engineering role at Fa Ewjt Saasfaprod1. Gurugram · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Set test direction and build cases from business and user needs, balancing hands-on checks with automation
- Check Azure pipelines across batch and streaming flows, tracing data from its origin through to its destination
- Verify Medallion-layer transformations, business rules, data accuracy, and the results shown in reports and dashboards
- Test Azure SQL and Data Lake storage, schemas, mappings, and models for integrity, reliability, and speed
- Write automated checks with SQL, Python, and PySpark; run load and scale tests and manage defects in Jira
What you bring
- A bachelor’s degree is required
- Hands-on work with Azure, Snowflake, DBT, Python, and PySpark
- A solid grasp of data warehousing, star schemas, data marts, and Medallion architecture
- Experience in Agile teams; P&C or specialty insurance knowledge is a plus
Who this fits
This role suits a data-testing engineer who can lead test planning and build automated checks across Azure data workflows. It is based in Gurugram with a hybrid arrangement.
From the employer
Data Quality Engineer – Azure Data Platform Testing
Overview
Seeking a seasoned Azure Data Engineer Tester to drive test strategy and ensure data quality across a large-scale Azure data platform modernization initiative. Data is a critical enterprise asset, and this role ensures accurate ingestion, transformation, storage, and reporting across cloud-based data solutions. The ideal candidate has test lead experience, strong automation skills, Agile exposure, and familiarity with P&C insurance domains.
Key Responsibilities
Test Strategy & Leadership
- Drive overall test strategy and create effective test cases and scenarios based on business and user requirements
- Define and implement test automation strategy, ensuring the right balance of manual and automated testing
- Participate in architecture, design, requirements, and code reviews; provide feedback to stakeholders
Azure Data Pipeline Testing
- Test Azure data pipelines built using services such as Microsoft Azure, Azure Data Factory, and Azure Synapse Analytics
- Validate end-to-end data movement from source to destination across batch and streaming workflows
Ensure Data Quality & Accuracy
- Validate ETL/ELT transformations across Medallion architecture layers
- Identify missing, duplicate, or incorrect data and ensure business rules are applied accurately
- Validate analytical outputs such as dashboards, reports, and data visualizations
Database & Storage Validation
- Test data stored in Azure SQL Database and Azure Data Lake Storage for integrity, reliability, and performance
- Validate schema, source-to-target mappings, and data models
Automation & Performance Testing
- Develop automated test scripts using SQL, Python, and PySpark
- Perform performance, scalability, and load testing of pipelines and data platforms
- Track defects and test cycles using Jira
Desired Skills & Competencies
Data & Technical Acumen
- Strong understanding of data warehousing concepts, star schemas, data marts, and Medallion architecture
- Ability to read data models and update source-to-target mapping documents
- Hands-on experience with Snowflake, Azure, DBT, Python, and PySpark
Industry & Methodology
- Experience working in Agile environments
- Knowledge of Property & Casualty (P&C) and Specialty Insurance is preferred
Key Responsibilities
Test Strategy & Leadership
- Drive overall test strategy and create effective test cases and scenarios based on business and user requirements
- Define and implement test automation strategy, ensuring the right balance of manual and automated testing
- Participate in architecture, design, requirements, and code reviews; provide feedback to stakeholders
Azure Data Pipeline Testing
- Test Azure data pipelines built using services such as Microsoft Azure, Azure Data Factory, and Azure Synapse Analytics
- Validate end-to-end data movement from source to destination across batch and streaming workflows
Ensure Data Quality & Accuracy
- Validate ETL/ELT transformations across Medallion architecture layers
- Identify missing, duplicate, or incorrect data and ensure business rules are applied accurately
- Validate analytical outputs such as dashboards, reports, and data visualizations
Database & Storage Validation
- Test data stored in Azure SQL Database and Azure Data Lake Storage for integrity, reliability, and performance
- Validate schema, source-to-target mappings, and data models
Automation & Performance Testing
- Develop automated test scripts using SQL, Python, and PySpark
- Perform performance, scalability, and load testing of pipelines and data platforms
- Track defects and test cycles using Jira
Bachelors Degree
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