Senior AI Architect, Semantic Layer – Algorithm

🕒 Agosto 31

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $120.000 - $150.000 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

👻 Score fantasma 1%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

Candidatar-se

Encontrar Vagas Remotas Similares

Configurar Alerta de Email para Novas Vagas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

Dynata

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

💼 Consultoria

📣 Marketing

☁️ SaaS

💰 $31.500.000 Debt Financing - Dynata em 2024-05

Consulting • Marketing • SaaS

A Dynata é uma empresa de pesquisa de mercado e dados que oferece painéis de pesquisa de primeira mão de alta qualidade, dados de audiência e um conjunto de plataformas de pesquisa e análises para ajudar organizações a coletar, ativar e mensurar insights. A empresa oferece painéis globais B2B e B2C, ferramentas de script e execução de pesquisas, enriquecimento de dados, ativação de audiência, medição de elevação de marca e visualização de dados, e enfatiza a qualidade dos dados usando IA/ML (QualityScore™) e certificações de segurança. A Dynata atende pesquisadores, marcas, agências de mídia, editores, institutos de pesquisa e acadêmicos com serviços tanto de autoatendimento quanto gerenciados.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

• 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