Job Description & How to Apply Below
Key Responsibilities Develop and implement test strategies, test cases, and automation scripts to validate data pipelines in Azure and Databricks.
Perform detailed data validation, reconciliation, and comparative analysis between source and target systems.
Validate ETL/ELT pipelines developed in Azure Data Factory (ADF) and Databricks.
Collaborate with Data Engineers and Product Owners to understand Source-to-Target Mapping (STM) and verify accurate transformation logic.
Monitor and validate data quality across Delta tables and Data Warehouses.
Identify data anomalies, document defects, and ensure resolution through collaboration with engineering teams.
Support CI/CD pipelines by embedding data testing within Dev Ops workflows.
Contribute to test data management, metadata validation, and regression testing processes.
Generate regular reports on test execution, defect trends, and QA health metrics.
Required Skills7+ years of experience in Data Quality Assurance and Testing within cloud-based data ecosystems.
Strong hands‑on experience with Azure Data Factory (ADF) and Databricks.
Proficiency in SQL and scripting languages such as Python.
Expertise in data profiling, reconciliation, and schema validation techniques.
Solid understanding of Slowly Changing Dimensions (SCD Type
2) and transformation logic.
Experience with Dev Ops tools like Azure Dev Ops or Git Hub Actions for CI/CD integration.
Familiarity with large datasets, performance testing, and data lineage tracking tools.
Preferred Skills
Experience with test automation frameworks for data validation.
Exposure to data governance and master data management (MDM) tools.
Knowledge of modern data warehouse architectures (Snowflake, Synapse, etc.).Certifications
Education
Bachelor’s degree in Computer Science, Information Systems, or a related field.#J-18808-Ljbffr
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