Data Engineer

🕒 Setembro 25

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🚰 Engenheiro de Dados

👻 Score fantasma 10%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Cognyte

1001 - 5000 funcionários

🔒 Cibersegurança

🔐 Segurança

🏛️ Governo

Cybersecurity • Security • Government

A Cognyte Software Ltd. é líder global em software de analytics investigativo que capacita diversos órgãos governamentais e outras organizações com inteligência acionável para um mundo mais seguro™. Nosso software de interface aberta é projetado para ajudar os clientes a acelerar e aumentar a eficácia das investigações e da tomada de decisões. Centenas de clientes confiam em nossas soluções para acelerar e conduzir investigações e extrair insights, com os quais identificam, neutralizam e enfrentam ameaças à segurança nacional e combatem diferentes formas de atividades criminosas e terroristas.

Descrição

• Design, develop, and maintain large-scale data ingestion, transformation, and enrichment pipelines • Build and operate distributed data processing services using Java, Python, Kafka, and related ecosystems • Design scalable, resilient, and high-performance data architectures • Develop and optimize data models for analytics, search, graph, and operational workloads • Deploy and manage applications across Kubernetes-based environments • Work with cloud-native services in AWS and/or GCP while supporting hybrid and on-premises deployments • Partner with customers, integration teams, and solution architects to deliver successful implementations • Monitor, troubleshoot, and optimize platform performance, reliability, and scalability • Contribute to infrastructure automation, CI/CD processes, and platform engineering initiatives • Travel domestically and internationally as needed for customer engagements, workshops, and deployments

🎯 Requisitos

• 5+ years of experience in Data Engineering, Software Engineering, or Platform Engineering • Strong programming experience in Java and/or Python • Hands-on experience with Kubernetes and containerized applications (Docker) • Experience working with AWS, GCP, or other public cloud platforms • Experience supporting or operating hybrid cloud and on-premises environments • Solid understanding of distributed systems and multithreaded applications • Experience with SQL and NoSQL databases • Experience building and operating production-grade data pipelines • Strong troubleshooting and operational skills • Excellent communication and collaboration skills • Experience designing and operating multi-cluster Kubernetes environments • Experience with data platforms deployed in highly regulated or air-gapped on-premises environments • Knowledge of networking, security, and cloud infrastructure best practices • Experience working directly with customer-facing engineering teams

🏖️ Benefícios

• Ability to travel domestically and internationally as needed for customer engagements, workshops, and deployments

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