Apply to Data Governance Analyst AI Enablement | Remote | W2 Only |

The Job

We are looking for a data-focused professional to help advance SCAN’s AI enablement and enterprise data governance. This role will improve the trust, usability, quality, and business meaning of data used for AI, analytics, reporting, and business decisions.

You will help build and govern enterprise data assets such as business glossaries, governed metrics, semantic layers, ontologies, knowledge graphs, metadata, data lineage, and stewardship practices.

You will work with data stewards, subject matter experts, platform teams, analytics teams, and business leaders to standardize business terminology, improve data quality, and make enterprise data easier for both people and AI tools to understand and use.

Responsibilities

• Develop and maintain dimensional models, hierarchies, semantic layers, and governed metrics.

• Support ontology and knowledge graph initiatives by identifying business entities, relationships, synonyms, and domain concepts.

• Govern and document data assets across Snowflake, Databricks, and Iceberg environments.

• Maintain and improve the enterprise data catalog, including metadata, lineage, ownership, usage, and business definitions.

• Improve data discoverability through tagging, business glossaries, metadata management, and workflow improvements.

• Perform data and metric validation for accuracy, completeness, consistency, aggregation logic, and timeliness.

• Use AI-assisted tools for documentation, analysis, data discovery, and governance activities.

• Work with business stakeholders, data stewards, SMEs, analytics teams, and data engineering teams on data governance and AI-readiness initiatives.

• Investigate data quality issues, perform root-cause analysis, document business impact, and work with technical teams on resolution.

• Participate in Agile/SAFe ceremonies and help prioritize and deliver governance initiatives.

• Improve governance automation, stewardship workflows, reporting certification, and AI-assisted governance.

• Support SCAN’s vision and goals and perform other duties as assigned.

Qualifications

• Bachelor’s degree in Information Systems, Data Analytics, Computer Science, Business Administration, Healthcare Administration, Statistics, or a related field. Equivalent experience may be considered.

• 3+ years of experience in data engineering, data governance, data management, data quality, analytics, BI, metadata management, knowledge management, or a related data role.

• Healthcare industry experience is strongly preferred, especially with Medicare Advantage, claims, member, provider, clinical, pharmacy, quality, medical economics, or operational data.

• Experience with semantic layers, ontologies, knowledge graphs, RAG, AI-assisted documentation, or metadata-driven discovery is preferred.

• Understanding of modern data warehouse and Lakehouse concepts, including cloud object storage, Iceberg/Delta Lake, metadata catalogs, data sharing, lineage, and governance.

• Experience using AI-assisted tools for documentation, analysis, data discovery, metadata quality, or governance.

• Experience with data catalogs, metadata management, data lineage, business glossaries, stewardship, and report certification.

• Experience with Power BI, Tableau, SSRS, or similar BI/reporting tools.

• Experience with CLI tools such as Cortex Code, Claude Code, or similar.

• Experience working in SAFe Agile or another Agile framework.

• Preferred certifications: CDMP, DGSP, DCAM, DAMA, Snowflake, Power BI, or Agile/SAFe certifications.

Key Skills

• Semantic layer and metrics governance

• Business glossaries and data dictionaries

• Ontologies, knowledge graphs, taxonomies, and domain models

• Strong SQL for data profiling, validation, reconciliation, and investigation

• Data catalogs, metadata, lineage, and stewardship

• Snowflake, Databricks, Iceberg/Delta Lake

• Power BI, Tableau, SSRS

• Data quality and root-cause analysis

• AI-assisted documentation and data discovery

• Healthcare data: claims, members, providers, clinical, pharmacy, quality, utilization, and finance

• Agile/SAFe delivery

• Ability to work with business, analytics, engineering, platform, stewardship, and leadership teams

Core Competencies

• Knowledge Management: Organize business definitions, relationships, ownership, and metadata.

• Business Partnership: Work effectively with technical and non-technical stakeholders.

• Analytical Thinking: Identify data issues, root causes, and business impact.

• Governance: Maintain standards for definitions, metadata, quality, lineage, and documentation.

• Communication: Explain complex data concepts clearly.

• Continuous Improvement: Improve governance, automation, data usability, and AI-assisted workflows.