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We are seeking a Senior Data Quality Engineer to join our dynamic team. This role is pivotal in ensuring the accuracy, consistency, and reliability of our enterprise data platforms, with a focus on cloud data engineering and automated data quality validation within Azure and Databricks environments. Your expertise will be crucial in building and maintaining robust automation and validation frameworks.

As a Senior Data Quality Engineer, you will be instrumental in:

- Designing, building, and deploying automated data quality and validation frameworks. - Executing data validation and regression testing across ingestion, transformation, and reporting layers. - Performing source-to-target reconciliation, metadata validation, and business rule checks. - Validating data integrity across key Azure services like Databricks, Data Lake, SQL, and Power BI. - Identifying, analyzing, and resolving data quality defects through root cause analysis. - Writing complex SQL queries for data validation and defect identification. - Creating and managing test data that aligns with functional and technical requirements. - Ensuring traceability from requirements to test cases for SIT and regression cycles. - Integrating data quality checks into CI/CD pipelines using GitHub and Jenkins. - Collaborating effectively with data engineers and analysts in an Agile/Scrum setting.

To excel in this role, you should possess:

- An undergraduate degree or equivalent experience. - A minimum of 6 years of dedicated experience in Data Quality Engineering or as a Data Automation Test Engineer. - Proven experience in building automation frameworks using Python. - Hands-on experience with validation methodologies similar to DVP or other custom automation frameworks. - Solid experience in Data Warehouse, ETL, and BI (Power BI) testing. - Familiarity with API testing. - Experience with metadata, lineage, and audit validation. - Expertise working with enterprise-scale cloud data platforms, including Azure Databricks, Azure Data Factory (ADF), Azure Data Lake, Azure SQL, and Azure Blob Storage. - Expert-level proficiency in SQL for data validation, reconciliation, and defect analysis. - A strong understanding of CI/CD and DevOps testing models, with knowledge of GitHub. - Sound knowledge of STLC, Agile, and SDLC methodologies. - Exposure to Selenium or other UI automation concepts is a plus.