Source description
About the role
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
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