Data Governance Specialist Jobs in Seattle, WA
Data Governance Specialist jobs in Seattle are concentrated in South Lake Union, the Central Business District, and Bellevue, across tech, healthcare, and financial services. Employers actively hiring right now include Databricks, Boeing, and TikTok. See the openings below and apply to the ones that match your experience.
Find JobsOverview
Open roles10
Top employerDatabricks
Work type75% On-site
Top credentialBachelor's
Companies hiring9
Showing 5 of 10+ Data Governance Specialist jobs
director, engineering – Data Governance & AI Experience
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Added 1w ago
Starbucks
director, engineering – Data Governance & AI Experience
Seattle, Washington
Added 1w ago
Lead Data Governance Technical Analyst
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Added 1w ago
Boeing
Lead Data Governance Technical Analyst
Seattle, Washington
Added 1w ago
Senior Manager, Data Operations & Governance
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Added 2w ago
Salesforce
Senior Manager, Data Operations & Governance
Seattle, Washington
Added 2w ago
Sr. Product Manager, Data Governance
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Added 3w ago
Databricks
Sr. Product Manager, Data Governance
Seattle, Washington
Added 3w ago
Senior Program Manager, AWS Data Center Procurement Governance (DCPG)
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Added 1mo ago
Amazon.com
Senior Program Manager, AWS Data Center Procurement Governance (DCPG)
Seattle, Washington
Added 1mo ago
Added 1w ago
director, engineering – Data Governance & AI Experience
Starbucks·Seattle, Washington
Job functions:
$208k - $363k/yr
10,000+ employees
Job Description
Now Brewing – 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
Basic Qualifications
- 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
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.
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.
Starbucks
director, engineering – Data Governance & AI Experience
Seattle, Washington
Added 1w ago10,000+ employees
Job functions:
$208k - $363k/yr
Job Description
Now Brewing – 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
Basic Qualifications
- 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
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.
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.
See All 10 Data Governance Specialist Jobs in Seattle
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Find JobsData Governance Specialist Job Market in Seattle
Who's Hiring
Top Industries Hiring
- Technology & Software
- Retail
- Transportation & Logistics
- E-Commerce & Online Marketplaces
Data Governance Specialist Jobs in Seattle: Frequently Asked Questions
How do I get a data governance specialist job in Seattle?
Focus your search on South Lake Union's tech corridor, the Central Business District's financial services firms, and the healthcare systems anchored around First Hill and the University District. Candidates with experience in cloud data platforms, regulatory compliance, and metadata management stand out in Seattle's market. Tailoring your resume to the specific industry, whether enterprise tech, health systems, or retail, gives you a concrete edge over generalist applicants.
Which companies hire data governance specialists in Seattle?
Companies currently hiring data governance specialists in Seattle include Databricks, Boeing, and TikTok, per current listings on Migrate Mate as of July 2026. Seattle's employer mix draws from large technology platforms, regional health systems, and financial institutions, all of which maintain active data governance programs to meet compliance and operational standards.
Are there remote data governance specialist jobs in Seattle?
Yes, though availability depends on the role. Data governance specialist work is largely analytical and policy-driven, making it more remote-friendly than hands-on technical positions. About 25% of data governance specialist openings tied to Seattle are remote or hybrid as of July 2026, with full-remote options most common in policy, documentation, and data stewardship functions rather than hands-on data engineering work.
How can I get a data governance specialist job in Seattle with little or no experience?
The most realistic entry path in Seattle is through a data analyst or data steward role at one of the city's mid-size tech firms or health systems, where governance functions are often shared across teams. University of Washington's data-focused programs produce strong local candidates, and many Seattle employers use contract-to-hire arrangements that let you build governance experience before moving into a dedicated specialist role. Certifications in data management, such as CDMP, help differentiate entry-level applicants in a competitive local pool.
Which industries hire the most data governance specialists in Seattle?
Most data governance specialist 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 enterprise technology companies, large regional health networks, and financial services firms creates sustained demand for specialists who can manage data quality, compliance, and lineage across complex, regulated environments.
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