director, engineering – Data Governance

Director of Engineering – Data Governance

From the beginning, Starbucks set out to be a different kind of company, one that celebrates connection and innovation. We’re looking for a Director of Engineering to lead enterprise data governance transformation, making trusted, well-understood data a foundation for confident decisions and meaningful business outcomes.

You’ll lead a multi-layered data governance organization, and an insights and business intelligence (BI) team, connecting ownership, quality, cataloging, metadata, lineage, context and semantic layers with trusted analytics. Success depends on influencing without direct authority, building shared accountability across federated teams and making governance practical, measurable and sustainable.

As a director, engineering, you will…

Lead enterprise governance transformation

• Establish an enterprise data governance maturity framework, baseline assessments and prioritized domain roadmaps. Lead execution across several cross-functional federated teams and demonstrate measurable improvement in enterprise maturity over time.
• Define outcomes and track progress in ownership and stewardship coverage, data quality, metadata and lineage completeness, control effectiveness and adoption. Use evidence to prioritize remediation and connect governance investment to business value.
• Develop focused data health cards that describe ownership and stewardship; quality, completeness, accuracy and freshness; lineage; metadata and business context; access and privacy constraints; and readiness gaps with accountable remediation plans.
• Use these health cards and governance controls to establish AI-ready data as a downstream outcome of trusted data foundations. Partner with consuming teams to assess fitness for intended use and address readiness gaps before data supports AI-enabled experiences.

Build cross-functional ownership and adoption

• Partner with business leaders, engineering, analytics, security and privacy to establish shared accountability with data domain owners and stewards. Bring partners together through governance councils to agree on priorities, decision rights, standards and issue resolution.
• Influence without direct authority across federated teams, resolve competing priorities and secure commitment to domain roadmaps. Lead change management, communication and enablement so governance becomes part of how partners build, manage and use data.

Develop AI-ready platforms

• Drive development of context layers, semantic layers, enterprise data cataloging, metadata management and end-to-end lineage. Make business definitions, data relationships, ownership and permitted use discoverable and consistent across domains.
• Operationalize governance policies and controls across the data lifecycle, including classification, access, privacy, retention and quality. Partner with security and privacy teams to balance trusted self-service with enterprise protection and compliance requirements.

Lead trusted insights and BI

• Lead an insights and BI team that translates business priorities into trusted reporting and actionable insights. Partner with domain owners to establish consistent metrics and governed semantic models, reducing conflicting definitions and fragmented reporting.
• Expand trusted BI and self-service through discoverable, documented and governed data products. Measure success through adoption, confidence in metrics and the business outcomes enabled by better decisions.

Scale engineering delivery and develop talent

• Manage and scale a high-performing org of engineering managers and senior ICs
• Lead globally distributed teams, including onshore/offshore engineering and vendors
• Foster a culture of ownership, innovation, and continuous improvement