Director, Data Product Engineering

🕒 Julho 27

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $200.000 - $245.000 / ano

⏰ Tempo Integral

🔴 Especialista

🧑‍💻 Engenheiro Full-stack

👻 Score fantasma 17%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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PayNearMe

201 - 500 funcionários

Fundada em 2009

💳 Fintech

☁️ SaaS

🤝 B2B

💰 $50.000.000 Series E - PayNearMe em 2025-09

Fintech • SaaS • B2B

A PayNearMe é uma empresa de tecnologia de pagamentos que oferece uma plataforma moderna e completa para que as empresas aceitem, distribuam e gerenciem pagamentos. A plataforma enfatiza o Gerenciamento da Experiência de Pagamento, oferecendo recursos como processamento de pagamentos moderno, automação e autosserviço, gerenciamento de exceções e uma rede de pagamento em dinheiro no varejo. A PayNearMe atende clientes empresariais em diversos setores (financiamento de automóveis e consumo, pedágios, iGaming, concessionárias "compre aqui, pague aqui", cooperativas de crédito, serviços hipotecários, escritórios de advocacia, etc. ) e divulga métricas incluindo mais de 16 anos de operação, mais de $50 bilhões processados anualmente, mais de 16. 000 empresas na sua plataforma e mais de 62. 000 locais de pagamento em dinheiro no varejo. Os serviços de transmissão de dinheiro são fornecidos por suas subsidiárias PayNearMe MT, Inc. e PayNearMe Financial, Inc.

Descrição

• We are seeking a strategic and technically accomplished Director, Data Products Engineering to lead the architecture, engineering, and delivery of AI products, data products and scalable data solutions across our fintech and payment processing ecosystem. • This leader will drive the company’s transition toward a product-centric data operating model by building trusted, reusable, scalable, and business-aligned AI/data products that power analytics, operational intelligence, AI/ML initiatives, customer experiences, regulatory reporting, and enterprise decision-making. • The role requires a strong combination of strategic data solution architecture expertise, modern cloud data engineering leadership, and product-thinking. The ideal candidate will lead teams responsible for engineering high-quality AI/data products, designing scalable data architectures, and enabling reliable enterprise data consumption at scale.

🎯 Requisitos

• Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Information Systems, or related field required; Master’s or PhD preferred. • 10+ years of progressive leadership experience in Data, Analytics, or AI/ML organizations. • 5+ years leading enterprise-scale analytics, data science, or AI engineering teams. • Strong hands-on expertise in predictive analytics, machine learning, recommendation systems, decision intelligence, and AI-enabled analytics. • Proven experience building scalable enterprise data products • Deep experience with modern cloud data platforms and analytical ecosystems including: • Snowflake • Dataiku • dbt • Fivetran • Apache Iceberg • Looker / LookML • Strong technical expertise in: • Python • SQL • ML frameworks and AI tooling • Cloud platforms such as AWS • Strong executive communication and stakeholder management skills. • Experience leading within complex, matrixed organizations. • Exceptional communication and stakeholder management skills with ability to influence executive and technical audiences.

🏖️ Benefícios

• Competitive salary and benefits with growth-company options grant • Fast- paced and professional work culture • Stock options with standard startup vesting - 1 year cliff; 4 years total • $50 monthly communication expense stipend to go towards your phone/internet bill • $250 stipend to enhance your WFH setup • Reimbursement for peripheral equipment: monitor (up to $400), keyboard and mouse (up to $200) • Premium medical benefits including vision and dental (100% coverage for employees) • Company-sponsored life and disability insurance • Paid parental bonding leave • Paid sick leave, jury duty, bereavement • 401k plan • Flexible Time Off (our team members typically take off ~3-4 weeks per year) • Volunteer Time Off • 13 scheduled holidays

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