In most industries, bad data costs money. In an academic medical center, trust in data underpins patient care, research integrity, and the metrics leadership runs the institution on.
We're hiring a **Data Quality Engineer** to build enterprise data quality for one of the most respected health systems in the world. You'll define quality standards, build semi-automated rule collection and sign-off workflows with business and technical stakeholders, implement scheduled and event-triggered quality scans, and wire quality checks directly into pipelines — so a failed upstream check can stop a downstream load before bad data spreads.
You'll need:
✔ 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
US-based, full-time W-2 with CitiusTech (no C2C). ~Monthly client-site travel, 3–4 days. August 2026 start.
If "silent data failure" is your villain origin story, apply below.
#DataQuality #DataObservability #DataEngineering #Hiring

Consultant - Data Quality Engineer

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