lead systems analyst, Data Stewardship (Seattle, WA)

Now Brewing – Stewardship Champions! #tobeapartner

From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.

Sitting within the Data Office, the Lead Analyst, Data Stewardship will help build and scale the enterprise data stewardship program by establishing clear ownership, practical governance processes, and tools that enable partners to confidently use and manage data. This role will collaborate across business and technology teams to embed stewardship into everyday ways of working, strengthen accountability for data quality, and foster a data-forward culture where trusted data informs decisions and drives business value.

As a Lead Analyst for the Stewardship Program, you will…

• Define the enterprise data stewardship operating model – Develop and maintain the stewardship framework, RACI, decision rights, and governance processes that clarify accountability across data domains.
• Establish accountable data ownership – Partner with business and technology leaders to identify, onboard, and support Data Owners and Data Stewards for priority domains.
• Build stewardship capability and engagement – Create role-based training, practical guidance, office hours, and a community of practice that enables stewards to perform consistently and effectively.
• Drive data-quality accountability – Define scorecards, escalation paths, and issue-management processes that help domain teams identify, prioritize, and resolve data-quality risks.
• Measure stewardship adoption and effectiveness – Track ownership coverage, metadata completion, steward participation, issue resolution, and other indicators to identify gaps and improve program outcomes.
• Coordinate governance decisions and domain rollout – Prepare recommendations, facilitate executive approvals, and manage phased implementation across priority data domains.