Senior Director – Enterprise Data Architect, Advertiser Intelligence Platform

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🕒 Setembro 1

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $170.000 - $180.000 / ano

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

👻 Score fantasma 9%

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LocaliQ

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

📣 Marketing

☁️ SaaS

🤝 B2B

Marketing • SaaS • B2B

A LocaliQ é uma plataforma de marketing digital e prestadora de serviços que ajuda empresas a aumentarem leads, receita e visibilidade online por meio de soluções de marketing multicanal baseadas em dados. A LocaliQ oferece publicidade paga (pesquisa, display, vídeo, social), SEO, gerenciamento de sites e listagens, marketing por e-mail segmentado, páginas de destino, gerenciamento de leads com inteligência artificial (Dash), relatórios e análises, além de expertise em marketing local gerenciado em diversos setores e empresas de múltiplas localizações. A empresa tem como público-alvo pequenas e médias empresas e agências com uma plataforma completa e serviços profissionais; métricas do site indicam grande escala: 283 milhões de leads gerados, $15,9 bilhões de receita total atribuída, 142 milhões de horas economizadas e mais de 512 mil empresas atendidas.

Descrição

• Define the enterprise architecture and phased roadmap for the Advertiser Intelligence Platform • Build the golden advertiser profile strategy and canonical data model • Architect AI enrichment, opportunity scoring, similarity matching, and predictive intelligence capabilities • Partner with engineering and product teams to deliver MVP through scale • Integrate insights into CRM, BI, and business workflows • Establish governance for data quality, privacy, lineage, explainability, and cost control • Work directly with GTM and operations leaders to ensure measurable business results • Define end-to-end platform architecture aligned with revenue growth, retention improvement, and faster decision-making • Establish multi-phase architecture spanning golden advertiser profiles, AI enrichment, similarity matching, intelligence UI, predictive analytics, and AI integration • Design canonical advertiser domain models, normalized schemas, and data products • Architect ingestion, harmonization, identity resolution, deduplication, quality controls, and lineage patterns • Lead AI-enriched intelligence, vectorized advertiser representations, peer matching, predictions, and recommendations • Lead discovery, architecture definition, MVP design, phased delivery, and production rollout • Review and contribute to schemas, interface contracts, orchestration logic, data quality rules, and implementation plans • Guide pilot execution, sales validation, feedback instrumentation, and post-MVP expansion • Integrate insights into CRM, BI, email workflows, and collaboration channels • Establish governance for enrichment costs, token and API budgets, privacy compliance, source transparency, and ROI reviews • Act as the senior technical voice across executives, product, engineering, commercial operations, and GTM stakeholders

🎯 Requisitos

• Deep enterprise data architecture experience in complex, cross-functional environments • Proven success building production-grade data and intelligence platforms • Strong background in cloud data ecosystems, modern analytics, and AI/ML-enabled architecture • Ability to lead at executive altitude and execute at implementation depth • Strong communication, influence, and operating discipline • 15+ years in enterprise data architecture, data platform engineering, analytics architecture, or closely related leadership roles, including ownership of complex cross-functional data programs • Experience designing enterprise-scale data architectures that unify multiple operational and platform systems into trusted, governed, production-ready domain models • Experience building or modernizing advertiser, customer, identity, martech, adtech, subscription, or revenue intelligence platforms • Experience with cloud data platforms and large-scale analytical ecosystems, ideally including BigQuery, modern orchestration patterns, semantic modeling, and near-real-time or daily refresh pipelines • Practical experience designing AI/ML-enabled data products, including feature design, scoring frameworks, recommender patterns, similarity matching, vector search, or predictive analytics • Experience translating ambiguous business goals into phased roadmaps, MVPs, architecture standards, and shipped capabilities adopted by business users • Experience partnering with sales, customer success, operations, finance, and product leaders to convert data strategy into business impact • Track record leading hands-on architecture reviews, mentoring engineers and architects, and unblocking execution in delivery-critical moments

🏖️ Benefícios

• Variable incentive compensation, including commissions, may be applicable