
1001 - 5000 funcionários
Fundada em 2004
🏢 Corporativo
📡 Telecomunicações
💰 $2.600.000 Post-IPO Debt em 2015-05
Enterprise • Telecommunications • Cloud
Arista Networks é líder na construção de redes escaláveis, de alto desempenho e com latência ultrabaixa para ambientes modernos de data centers e computação em nuvem. A empresa oferece uma ampla gama de soluções de networking, incluindo o Arista Extensible Operating System (EOS) para cloud networking, o CloudVision para automação e visibilidade de redes, e uma variedade de switches e plataformas de roteamento de alto desempenho. As soluções da Arista são projetadas para redes WAN empresariais, roteamento em nível de nuvem, segmentação multi-domínio, segurança e modelos modernos de operação de rede, tornando-se uma escolha crucial para data centers de grande escala e ambientes de nuvem.
🕒 Julho 16
🗣️🇺🇸🇬🇧 Inglês obrigatório
Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

1001 - 5000 funcionários
Fundada em 2004
🏢 Corporativo
📡 Telecomunicações
💰 $2.600.000 Post-IPO Debt em 2015-05
Enterprise • Telecommunications • Cloud
Arista Networks é líder na construção de redes escaláveis, de alto desempenho e com latência ultrabaixa para ambientes modernos de data centers e computação em nuvem. A empresa oferece uma ampla gama de soluções de networking, incluindo o Arista Extensible Operating System (EOS) para cloud networking, o CloudVision para automação e visibilidade de redes, e uma variedade de switches e plataformas de roteamento de alto desempenho. As soluções da Arista são projetadas para redes WAN empresariais, roteamento em nível de nuvem, segmentação multi-domínio, segurança e modelos modernos de operação de rede, tornando-se uma escolha crucial para data centers de grande escala e ambientes de nuvem.
• Define Enterprise Data Architecture across Fabric, Data Lake, EDW, and analytics platforms. • Design Integration Patterns for ingestion, transformation, and consumption. • Create architectural flows and reference models. • Establish standards for data modeling, metadata, lineage, and governance. • Implement data validation, logging, monitoring, lineage, and RBAC. • Ensure compliance with enterprise security, confidentiality, and regulatory standards. • Drive platform cost optimization, performance tuning, and operational excellence. • Enforce architectural governance and adherence to standards. • Collaborate with business stakeholders and source system teams to understand data requirements. • Translate business needs into technical specifications and architectural roadmaps. • Review user stories and provide architectural guidance to development teams. • Support QA and functional teams in defining testing strategies for new and existing features. • Ensure delivered solutions align with business needs and architectural intent. • Integrate AI/ML Models and GenAI capabilities into data products and workflows. • Evaluate emerging technologies and recommend adoption strategies. • Guide teams on responsible AI usage and integration patterns. • Conduct root cause analysis for data issues and identify opportunities for improvement. • Manage platform reliability, data quality, and governance processes. • Define the continuity strategy for all data and integration platforms, not just implement it. • Proactively identify architectural risks.
• 10+ years in enterprise solution architecture, data engineering, and software development. • Degree preferably in Computer Science, Information Technology, Management Information Systems, or Accounting. • Proven experience designing end-to-end integrations, data platforms, and automation for large enterprise environments. • Strong hands-on expertise with Microsoft Fabric, Data Lake, Data Warehouse, Data Pipelines, and the broader Microsoft ecosystem. • Deep experience with Power BI semantic models, datasets, dashboards, and reporting. • Advanced proficiency in DAX, Power Query, SQL, Python, and PySpark. • Demonstrated experience architecting ETL/ELT pipelines integrating diverse data sources into Azure Data Lake and EDW. • Strong understanding of data modeling, normalization, metadata management, and enterprise data security. • Exposure to AI/ML, Copilot, GenAI, LLMs, prompt engineering, and AI API integration. • Familiarity with SDLC, software quality practices, Jira, Git, CI/CD. • Experience with SaaS/Cloud ERP or CRM systems (NetSuite, Salesforce, SAP S/4HANA). • Excellent communication, stakeholder management, and problem-solving skills.
• Health insurance • 401(k) matching • Paid time off • Flexible working hours • Professional development opportunities
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