Data Quality Engineer-Azure Data Platform Testing

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 .