Summit Human Capital is seeking a highly skilled Sr. Data Quality Engineer with a strong foundation in data engineering and governance. This individual will play a key role in operationalizing data governance policies and ensuring accuracy, consistency, and compliance across modern cloud-based data systems. The ideal candidate will design and implement automated data validation frameworks, develop dashboards for monitoring data quality, and embed quality controls into AWS pipelines to maintain secure, high-quality data flows across the organization.
Requirements:
Proven experience in data engineering with a deep emphasis on data quality frameworks and governance.
Proficiency with AWS services such as Glue, Athena, Lambda, and RDS for automation, processing, and monitoring.
Strong Python development skills for building validation scripts, workflows, and lifecycle automation.
Familiarity with data governance frameworks such as DAMA-DMBOK or NIST, and experience translating those into operational policies.
Ability to design intuitive visualization dashboards for tracking and reporting on data quality metrics.
Develop and automate data quality rules, anomaly detection, and monitoring dashboards using AWS services.
Responsibilities:
Build and maintain visualization tools to track data accuracy, completeness, and timeliness across data systems.
Operationalize data governance policies through tagging, lifecycle management, and retention automation.
Create and refine workflows for data intake, validation, approval, and archival processes.
Implement secure access controls such as SSO, Cognito, and RBAC to protect data pipelines and quality systems.
Integrate data quality checks into AWS-based data and machine learning workflows to ensure trusted, compliant outcomes.
