Data Quality Engineer

This role is for one of the Weekday's clients Min Experience: 3 years JobType: full-time We are seeking a skilled and detail-oriented Data Quality Engineer to ensure the accuracy, reliability, and consistency of data across enterprise data platforms.
This role is critical to maintaining high standards of data integrity as data moves through complex ETL pipelines and is consumed by analytics, reporting, and downstream business systems.
As a Data Quality Engineer, you will work closely with data engineers, analytics teams, and business stakeholders to define data quality rules, validate ETL processes, and proactively identify issues before they impact decision-making.
This full-time role is ideal for someone with strong experience in Snowflake-based data environments, hands-on ETL validation, and a passion for building trustworthy data systems.
Key Responsibilities Design, implement, and execute data quality checks across ETL pipelines to ensure completeness, accuracy, consistency, and timeliness of data Validate data ingestion, transformation, and loading processes in Snowflake environments Perform end-to-end ETL testing, including source-to-target validation, transformation logic checks, and reconciliation testing Develop automated and manual test cases to validate data pipelines and business rules Monitor data quality metrics and dashboards, identifying anomalies, data drifts, and pipeline failures Collaborate with data engineers to troubleshoot ETL failures and data discrepancies Define data quality rules, thresholds, and acceptance criteria in alignment with business requirements Ensure data integrity across multiple data sources, warehouses, and downstream reporting systems Support data release cycles by validating new ETL workflows, schema changes, and enhancements Document data quality processes, test scenarios, and validation results for audit and compliance purposes Work closely with analytics and business teams to understand data usage patterns and critical data dependencies Proactively identify opportunities to improve ETL reliability, performance, and observability Contribute to continuous improvement of data governance, validation frameworks, and quality standards What Makes You a Great Fit Minimum 3 years of experience in data quality engineering, ETL testing, or data validation roles Strong hands-on experience with Snowflake as a cloud data warehouse Solid understanding of ETL concepts, data pipelines, and data warehousing architectures Proven experience in ETL testing, including data reconciliation, transformation validation, and error handling Strong SQL skills for querying, validating, and analyzing large datasets Experience working with structured and semi-structured data across multiple source systems Familiarity with data quality frameworks, validation tools, or custom testing approaches Strong analytical and problem-solving skills with high attention to detail Ability to work cross-functionally with data engineers, analysts, and business stakeholders Experience identifying root causes of data issues and driving corrective actions Clear communication skills, with the ability to explain data issues to both technical and non-technical audiences Self-driven mindset with the ability to manage multiple data validation efforts simultaneously