Enterprise Data & AI Governance Lead

SCAN Group; Long Beach (CA); On-site; USD 80,000 - 138,000; Full time

Benefits offered by this job

Annual bonus program

Generous PTO

401(k) retirement plan with employer 1

Tuition reimbursement

Job summary

SCAN Group is seeking a data governance professional to advance AI enablement and enterprise data governance. You will build semantic foundations, govern data assets, and partner with business and technical teams to improve data quality and AI-ready analytics.

The role focuses on Snowflake, Databricks, and Iceberg environments, with a strong emphasis on metadata, glossaries, and governance workflows in a healthcare data context.

Qualifications

• 3+ years in data engineering, governance, or analytics.
• Experience in healthcare data environments preferred.
• Knowledge management techniques like ontologies and knowledge graphs encouraged.
• Familiarity with warehouse/open lakehouse concepts and metadata catalogs.
• Proficiency with BI tools and AI-assisted documentation beneficial.
• SAFe or Agile delivery experience; relevant certifications valued.

Responsibilities

• Govern and document data assets across Snowflake, Databricks, and Iceberg.
• Develop semantic layers, dimensional models, and governed metrics.
• Enrich data catalogs with metadata, lineage, and ownership context.
• Collaborate with data stewards, analytics, and platform teams to enable AI-ready data.
• Perform data and metric validation; improve data quality and trust.

Skills

Data governance

Knowledge management

SQL

Snowflake

Power BI

Tableau

SAFe Agile

Metadata management

Education

Bachelor's degree in information systems or related field

Tools

Snowflake

Databricks

Iceberg

Power BI

Tableau

SSRS

Job description

SCAN Group is seeking a data governance professional to advance AI enablement and enterprise data governance. You will build semantic foundations, govern data assets, and partner with business and technical teams to improve data quality and AI-ready analytics.

The role focuses on Snowflake, Databricks, and Iceberg environments, with a strong emphasis on metadata, glossaries, and governance workflows in a healthcare data context.