What are the responsibilities and job description for the Sr Semantic Enggineer position at Apolis?
Role: Sr Semantic Enggineer
Work location: Seattle, WA US / Remote
Project Overview
As a Senior Semantic Strategist, you will be responsible for championing the needs and goals of our business users by defining, executing, and perfecting metadata models and information architectures to support client's data strategy.
This is a highly collaborative role for a thought leader with experience building a metadata or semantic practice in a large enterprise. This person will work cross-functionally with subject matter experts (SMEs), product managers, and business leaders to define and implement information architectures that enable search, discovery, and interoperability of client's data assets.
Key Responsibilities
• Collaborate with the semantic engineering team to drive the vision, roadmap, and execution of a semantic data practice, ensuring alignment with enterprise governance and data management strategies.
• Partner with business and technical stakeholders to develop and document a metadata flow architecture that traces metadata through the data ecosystem.
• Proactively engage and work with product teams, data stewards, engineers, and business leaders to translate metadata requirements into semantic data models.
• Design, validate, and formalize information models including taxonomies, ontologies, and metadata frameworks that enhance data discovery and usability.
• Develop and promote best practices for structuring and describing enterprise data products to enable better search, discovery, and integration across platforms.
• Serve as a thought leader and advocate for semantic technologies, staying informed about industry trends in semantic modeling, metadata management, and information architecture.
• Work closely with enterprise data governance teams to ensure semantic models support compliance, security, and interoperability standards.
Qualifications
• 10 years of experience in semantic strategy, knowledge management, or enterprise data modeling.
• Strong track record of influencing enterprise-wide semantic adoption through strategic vision and advocacy.
• Proficiency in modern metadata management tools and techniques and sound understanding of enterprise metadata management frameworks and/or semantic standards.
• Experience designing data models that enhance data search, discoverability, and governance.
• Exceptional ability to work with business leaders, SMEs, and cross-functional teams to translate domain expertise into structured knowledge models.
• Ability to articulate complex concepts to both technical and non-technical audiences, advocating for best practices in semantic data management.
• Excellent communication skills - be an effective, passionate, trusted advocate and communicator for metadata management, data catalogs, and semantic technologies.
• High level of motivation, self-starter, ability to demonstrate effective project management and completion of complex network tasks with little guidance.
• Experience in particular technologies is less important than proven ability in data modeling, design, creative problem-solving, and execution.
Skills
Data collection,data engineering,data model,data model design,database,database design,information technology,management,operational management,semantic data model,technology
Work location: Seattle, WA US / Remote
Project Overview
As a Senior Semantic Strategist, you will be responsible for championing the needs and goals of our business users by defining, executing, and perfecting metadata models and information architectures to support client's data strategy.
This is a highly collaborative role for a thought leader with experience building a metadata or semantic practice in a large enterprise. This person will work cross-functionally with subject matter experts (SMEs), product managers, and business leaders to define and implement information architectures that enable search, discovery, and interoperability of client's data assets.
Key Responsibilities
• Collaborate with the semantic engineering team to drive the vision, roadmap, and execution of a semantic data practice, ensuring alignment with enterprise governance and data management strategies.
• Partner with business and technical stakeholders to develop and document a metadata flow architecture that traces metadata through the data ecosystem.
• Proactively engage and work with product teams, data stewards, engineers, and business leaders to translate metadata requirements into semantic data models.
• Design, validate, and formalize information models including taxonomies, ontologies, and metadata frameworks that enhance data discovery and usability.
• Develop and promote best practices for structuring and describing enterprise data products to enable better search, discovery, and integration across platforms.
• Serve as a thought leader and advocate for semantic technologies, staying informed about industry trends in semantic modeling, metadata management, and information architecture.
• Work closely with enterprise data governance teams to ensure semantic models support compliance, security, and interoperability standards.
Qualifications
• 10 years of experience in semantic strategy, knowledge management, or enterprise data modeling.
• Strong track record of influencing enterprise-wide semantic adoption through strategic vision and advocacy.
• Proficiency in modern metadata management tools and techniques and sound understanding of enterprise metadata management frameworks and/or semantic standards.
• Experience designing data models that enhance data search, discoverability, and governance.
• Exceptional ability to work with business leaders, SMEs, and cross-functional teams to translate domain expertise into structured knowledge models.
• Ability to articulate complex concepts to both technical and non-technical audiences, advocating for best practices in semantic data management.
• Excellent communication skills - be an effective, passionate, trusted advocate and communicator for metadata management, data catalogs, and semantic technologies.
• High level of motivation, self-starter, ability to demonstrate effective project management and completion of complex network tasks with little guidance.
• Experience in particular technologies is less important than proven ability in data modeling, design, creative problem-solving, and execution.
Skills
Data collection,data engineering,data model,data model design,database,database design,information technology,management,operational management,semantic data model,technology
