Data Quality Engineer

Key Responsibilities

·         Design and implement automated data quality checks, validation rules, and monitoring frameworks.

·         Validate data accuracy, completeness, consistency, freshness, and integrity across ETL/ELT pipelines.

·         Perform data profiling, anomaly detection, reconciliation, duplicate analysis, and business-rule validation.

·         Validate source-to-target mappings, crosswalk/reference data, and migration/integration processes.

·         Perform root cause analysis and collaborate with data engineering and business teams to resolve data defects.

·         Build data quality dashboards, reports, and automated controls.

·         Support data governance, audit, regulatory requirements, and quality sign-offs.

Required Skills

·         Strong experience in Data Quality Engineering / Data Validation.

·         Advanced SQL skills and hands-on Snowflake experience, including tables, views, profiling, and query optimization.

·         Experience with ETL/ELT pipelines and data warehouses.

·         Strong understanding of data quality frameworks, reconciliation, unit/integration testing, metadata, and data lineage.

·         Experience working with large and complex datasets.