Citius Healthcare Consulting is hiring a Data Quality Engineer to build enterprise data quality for one of the most respected health systems in the world. The role involves defining quality standards, implementing quality scans, and ensuring data integrity in patient care and research.
Responsibilities:
- Define quality standards
- Build semi-automated rule collection and sign-off workflows with business and technical stakeholders
- Implement scheduled and event-triggered quality scans
- Wire quality checks directly into pipelines
- A failed upstream check can stop a downstream load before bad data spreads
Requirements:
- 7+ years in data engineering/quality engineering
- Hands-on DQ implementation across cloud platforms (BigQuery, Fabric/Azure SQL); Dataplex DQ, Purview, Collibra DQ, or comparable observability tooling
- Pipeline integration patterns — quality gates in Dataflow, ADF/Dataflow Gen2, dbt/Dataform-style transforms
- Alerting and remediation workflow design (human + system consumers)
- Strong SQL and Python; you write reusable sample code and documentation