Senior AI Architect, Semantic Layer – Algorithm

🔥 12 hours ago

🇺🇸 United States – Remote

💵 $120k - $150k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

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Dynata

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

💼 Consulting

📣 Marketing

☁️ SaaS

💰 $31.5M Debt Financing - Dynata on 2024-05

Consulting • Marketing • SaaS

Dynata is a market research and data company that provides high-quality first-party survey panels, audience data, and a suite of survey and analytics platforms to help organizations collect, activate, and measure insights. The company offers global B2B and B2C panels, survey scripting and fielding tools, data enrichment, audience activation, brand lift measurement, and data visualization, and it emphasizes data quality using AI/ML (QualityScore™) and security certifications. Dynata serves researchers, brands, media agencies, publishers, pollsters, and academics with both self-service and managed services.

📋 Description

• Define and evolve the technical architecture for Dynata's semantic layer, medallion architecture, and enterprise data models • Translate business concepts, governance standards, and domain definitions into scalable technical frameworks and enforceable architectures • Establish standards for schema design, metadata management, interoperability, and semantic consistency across the platform • Ensure analytical, operational, and AI use cases are supported by a common architectural foundation • Design and govern data contract frameworks for reliable, reusable, and trusted data assets • Establish standards for schema validation, versioning, lineage, quality controls, and controlled evolution of enterprise datasets • Partner with governance stakeholders to operationalize policies through technical controls and platform capabilities • Promote consistency, traceability, and discoverability across enterprise data assets • Define architectural patterns for feature stores, model inputs and outputs, model lifecycle management, and algorithm interoperability • Establish standards for integrating analytical models, machine learning solutions, and AI services with enterprise data assets • Design scalable frameworks for feature reuse, model governance, and algorithm deployment • Ensure AI and machine learning capabilities use secure, governed, and reusable platform foundations • Partner with Product, Technology, Research & Data Science, and Data Platform teams • Translate complex technical concepts into architectural decisions and implementation guidance • Lead architecture discussions balancing business needs, governance requirements, technical feasibility, and long-term scalability • Serve as a technical thought leader on semantic architecture, data governance, AI enablement, and enterprise platform design • Report to the VP, Research & Data Science

🎯 Requirements

• 7+ years of experience in data architecture, platform architecture, AI/ML infrastructure, data engineering, or related fields • Proven experience designing enterprise-scale semantic layers, data models, schema governance frameworks, or data contract architectures • Strong understanding of modern lakehouse architectures, medallion design patterns, metadata management, and data governance principles • Demonstrated experience architecting machine learning and AI platforms, including feature stores, model lifecycle management, lineage, and governance capabilities • Experience establishing technical standards that support analytics, machine learning, and AI-driven applications at scale • Strong understanding of schema management, metadata frameworks, versioning strategies, and interoperability patterns • Experience translating ambiguous business requirements and governance concepts into scalable technical architectures • Strong communication and stakeholder management skills, including experience influencing technical leaders, architects, and executive stakeholders • Demonstrated success operating effectively in ambiguous environments and leading foundational platform and architecture initiatives • Experience with modern data and AI platforms such as Databricks, DataHub, Snowflake, feature stores, metadata platforms, or comparable technologies • Preferred: Experience implementing or governing enterprise semantic layers and business glossaries • Preferred: Familiarity with AI governance, model governance, and responsible AI frameworks • Preferred: Experience designing architecture for graph analytics, forecasting, optimization, or decision-support systems • Preferred: Exposure to LLM-enabled platform capabilities such as metadata generation, semantic modeling, catalog enrichment, or governance automation

🏖️ Benefits

• A discretionary incentive program may be provided as part of the compensation package • Full range of medical and other benefits, dependent on full-time employment status • Inclusive and accessible work environment • Accommodations available upon request for all aspects of the selection process