Director Of Data Governance Jobs in Seattle, WA
Director Of Data Governance jobs in Seattle are concentrated in South Lake Union, the Central Business District, and Bellevue's tech corridor, with strong demand from technology, healthcare, and financial services employers. Companies actively hiring include Databricks, Boeing, and TikTok. See the openings below and apply to the ones that match your experience.
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Showing 5 of 10+ Director Of Data Governance jobs
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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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law.
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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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law.
See All 10 Director Of Data Governance Jobs in Seattle
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Find JobsDirector Of Data Governance Job Market in Seattle
Who's Hiring
Top Industries Hiring
- Technology & Software
- Retail
- Transportation & Logistics
- E-Commerce & Online Marketplaces
Director Of Data Governance Jobs in Seattle: Frequently Asked Questions
How do I get a director of data governance job in Seattle?
Target Seattle's dominant hiring sectors: enterprise technology firms in South Lake Union, health systems anchored around First Hill and the broader Puget Sound region, and financial services and insurance companies based in the Central Business District. Candidates with hands-on experience building data governance frameworks, familiarity with cloud-native data platforms, and a background in regulated industries gain a clear edge in Seattle's market, where large-scale data compliance and AI readiness are top priorities.
Which companies hire director of data governances in Seattle?
Companies currently hiring director of data governances in Seattle include Databricks, Boeing, and TikTok, per current listings on Migrate Mate as of July 2026. Seattle's hiring base skews toward large technology companies, integrated health systems, and financial institutions that manage complex, high-volume data environments requiring formal governance leadership.
Are there remote director of data governance jobs in Seattle?
Yes, and director of data governance roles lean toward remote and hybrid arrangements more than most leadership positions because the work is primarily strategic, analytical, and cross-functional rather than tied to physical infrastructure. About 25% of director of data governance openings tied to Seattle are remote or hybrid as of July 2026. Policy development, stakeholder alignment, and framework design are the responsibilities most commonly performed off-site by Seattle-based professionals.
How can I get a director of data governance job in Seattle with little or no experience?
The most realistic entry path in Seattle is moving laterally from a data analyst, data steward, or data quality manager role inside one of the city's large technology or healthcare organizations, which frequently promote from within. Seattle employers such as major health systems and cloud platform companies often post governance program manager or data steward roles that build directly toward director-level work. Demonstrating familiarity with metadata management tools, GDPR or HIPAA compliance, and cross-departmental data policy work strengthens a candidate's profile locally.
Which industries hire the most director of data governances in Seattle?
Most director of data governance openings in Seattle sit in Technology & Software, Retail, and Transportation & Logistics, per current listings on Migrate Mate as of July 2026. Seattle's concentration of global technology headquarters, major regional health networks, and financial services firms creates sustained demand for governance leadership in sectors where data quality, regulatory compliance, and enterprise-scale data strategy directly affect core operations.
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