director, engineering - Data Governance & AI Experience

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 the next generation of enterprise data platforms and AI-ready systems, shaping how data is governed, discovered, and activated across the company.

This role will define and scale critical capabilities across data governance, catalog, semantic layer, metadata, and AI data readiness, powering intuitive, self-serve experiences such as natural language to SQL and data exploration.

You’ll lead a multi-layered engineering organization (engineering managers, data engineers, ML engineers, and contractors) to deliver high-impact, scalable platforms that unify data, AI, and user experience.

As a director, engineering, you will…

Governance & Architecture Leadership

• Own the vision, architecture, and execution of enterprise data platform capabilities, including:
• Data governance & stewardship frameworks
• Enterprise data catalog & discovery
• Semantic layer and context modeling
• Metadata management & lineage systems
• AI-ready data pipelines and feature readiness
• Build a cohesive data & AI experience layer enabling self-serve analytics and intelligent applications
• Drive development of natural language to SQL and conversational data interfaces

AI & Data Experience Innovation

• Enable agent-driven and AI-assisted data interactions, accelerating decision-making across partners and leadership
• Partner with data science teams to operationalize ML-ready datasets, feature stores, and experimentation platforms
• Modernize data access patterns to support self-service at scale while maintaining governance and trust

Engineering Execution & Scale

• Lead multiple engineering managers and distributed teams (onshore/offshore, FTE + contract)
• Drive delivery of scalable, reliable platforms supporting enterprise-wide data usage
• Establish engineering standards for performance, reliability, observability, and data quality

Governance, Trust & Compliance

• Operationalize data governance policies, controls, and standards across all platforms
• Ensure alignment with privacy, security, and regulatory requirements
• Balance self-service access with enterprise-grade data controls

Cross-Functional Leadership

• Partner with data science, product, analytics, and business leaders to translate needs into scalable platform capabilities
• Drive alignment across data platform, BI, and AI initiatives to reduce fragmentation
• Influence senior leadership with clear articulation of technical strategy and business value

Talent & Organization

• Build 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

We’d love to hear from leaders who…

• Have deep expertise in data platforms, governance, metadata, and semantic modeling
• Have built self-service data ecosystems with strong adoption across business users
• Understand both AI/ML lifecycle needs and enterprise data architecture
• Have delivered platforms enabling natural language querying, data discovery, and analytics democratization
• Can integrate fragmented data systems into unified, scalable architectures

Artificial Intelligence (AI), Artificial Intelligence (AI), Metadata, SQL (Structured Query Language), Engineering Management, User Interface/Experience (UI/UX), Leadership, Enterprise Architecture, Training Data Sets, Data Science, * 12+ years in data/platform/software engineering

• 5+ years leading engineering managers and large distributed teams
• Proven experience building enterprise-scale data platforms (governance, catalog, semantic layer)
• Hands-on expertise with modern data stacks (cloud, batch/streaming, metadata systems)
• Strong executive communication and stakeholder alignment skills

Preferred Qualifications

• Experience with AI-driven data platforms, LLM-powered interfaces, or agent frameworks
• Experience delivering natural language to SQL or conversational analytics solutions
• Deep understanding of data governance, lineage, and compliance frameworks
• Experience in retail, supply chain, or high-scale operational environments
• Demonstrated track record of driving enterprise transformation and platform adoption