Intuit
Principal, Finance Data Governance & Strategy
$215K–$291K
Mountain View, California +1 · Principal · Full-time · Posted Sep 15, 2026
- Location
- Mountain View, California
San Diego, California - Experience
- 8+ years in data governance, data strategy, or data architecture, including 2 to 3 years operating at a principal or strategic level.
- Education
- Bachelor's degree in Information Systems, Computer Science, Finance, Business, or a related field; advanced degree or relevant certifications a plus.
About the job
Owns Finance’s data governance strategy and technical foundation, including data stewardship, lineage, controls, synthetic data, and governance for platform modernization.
What you'll do
- Define and operate Finance data governance standards, stewardship, ownership, quality, and access controls.
- Build and maintain Finance data maps and lineage, and lead governance and reconciliation strategy for ERP and planning platform migration.
- Set Finance’s synthetic data strategy and partner across teams on privacy-conscious data controls and enterprise data strategy.
What they ask for
- 8+ years in data governance, data strategy, or data architecture, including 2 to 3 years at a principal or strategic level.
- Demonstrated experience standing up or scaling a data governance and stewardship program.
- Experience governing data through a large legacy-to-cloud platform migration and owning enterprise data maps, catalogs, and lineage tooling.
- Strong technical fluency, including SQL and modern data warehouse environments; experience in a regulated or controls-sensitive environment.
Nice to have
- Hands-on experience with synthetic data generation and validation techniques.
- Experience with Oracle ERP or EPM environments, Finance data models, or supporting Finance, Accounting, or FP&A in a large enterprise.
Pay
USD 215,000 - USD 291,000 base salary
Tools
SQL, Snowflake, BigQuery, Oracle ERP, EPM
AI focus
Lead Finance’s synthetic data strategy for testing, development, model training, and analytics; evaluate AI-driven data quality and support AI/ML data readiness.
Model-written summary · the original posting is authoritative