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[Remote] Data Quality Lead, Data Governance
Note: The job is a remote job and is open to candidates in USA. Baylor Scott & White Health is seeking a Data Quality Lead to join their A&I Data Governance team. This senior role focuses on ensuring data trustworthiness and operationalizing data quality standards across various domains, while collaborating with analytics and MDM teams to enhance data governance practices.
Responsibilities
- Support enterprise data quality frameworks across federated clinical, operational, and financial domains by helping define standards, controls, and shared expectations for CDEs, clinical metrics, regulatory reporting, and AI‑ready data
- Guide and enable data stewards and domain teams in using Ataccama ONE for data quality rule governance, glossary stewardship, metadata completeness, lineage visibility, issue logging, and domain accountability
- Build and inform DQ monitoring approaches including dashboards, scorecards, and issue‑management structures that domains use to track quality, transparency, and stewardship performance
- Partner with analytics, IT, and domain leaders to drive consistent adoption of DQ governance practices across federated teams, ensuring alignment with organizational priorities, regulatory expectations, and clinical/operational workflows
- Collaborate with MDM governance teams to ensure high‑quality healthcare master data (Patient, Provider, Location, Encounter) through aligned standards for matching/merging, golden records, survivorship rules, and reference‑data stewardship
- Support transparent incident reporting and root‑cause analysis by ensuring federated teams follow Ataccama‑based workflows and governance processes for documenting, evaluating, and resolving DQ issues
- Communicate DQ risks and requirements clearly to domain stakeholders, highlighting impacts on patient safety, quality reporting, operational performance, and enterprise analytics/AI initiatives
- Influence adoption of governance and DQ standards across analytic, clinical, and operational teams by reinforcing guardrails, stewardship responsibilities, and the value of trusted data
- Find improvements to data quality and stewardship workflows, helping refine operating models and processes that enhance consistency, accountability, and transparency across federated domains
- Mentor peers and junior team members to strengthen organizational literacy in data quality, metadata, lineage, and governance practices
- Evaluate emerging tools and methods including GenAI‑supported DQ signals, anomaly detection for clinical measures, lineage automation, and metadata enrichment to recommend enhancements to the enterprise DQ framework
- Monitor trends in data governance, healthcare data quality maturity, and AI safety, integrating relevant advancements into DQ standards, stewardship practices, and Ataccama governance patterns
Skills
- EDUCATION - Bachelor's or 4 years of work experience above the minimum qualification
- EXPERIENCE - 5 Years of Experience
- 5+ years in data quality in complex or federated data governance environments
- Experience implementing enterprise DQ programs, policies, standards, and controls across multiple domains
- Advanced SQL for interpreting data structures, validation logic, and understanding profiling/anomaly‑detection outputs (not a daily SQL role)
- Experience creating DQ dashboards/KPIs for stewardship or program monitoring
- Working knowledge of data lineage and impact analysis concepts and tools
- Strong ability to influence cross‑functional stakeholders (analytics, IT, clinical, operational)
- CDMP, DAMA, or equivalent
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