Data Engineer

🔥 16 hours ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

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Logo of Cognyte

Cognyte

1001 - 5000 employees

🔒 Cybersecurity

🔐 Security

🏛️ Government

Cybersecurity • Security • Government

Cognyte is a global leader in investigative analytics software, empowering government and other organizations with Actionable Intelligence for a safer world. With thirty years of proven market leadership, Cognyte provides solutions that enable customers in over 100 countries to accelerate investigations, derive insights, and neutralize threats to national security. The company's robust and open analytics platform offers a broad portfolio of solutions addressing security challenges, helping teams connect the dots and resolve investigations quickly. By delivering tools for decision intelligence, network intelligence, operational intelligence, and threat intelligence, Cognyte supports the quick detection and mitigation of threats, ensuring high-quality and conclusive investigative outcomes.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

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

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