Cognyte
Cognyte
1,001 – 5,000 Employees
CybersecurityGovernmentSecurity
Cognyte develops investigative analytics software for government agencies and other organizations focused on security and threat response. Its open analytics platform brings together decision, network, operational, and threat intelligence, helping teams connect disparate information, accelerate investigations, and identify or mitigate risks. With three decades of market experience and customers in more than 100 countries, Cognyte supports investigative work across national security and broader security operations.

Mid-Senior Data Engineer, Remote in the United States - Cognyte

Build scalable data pipelines and distributed platforms supporting Cognyte’s criminal, terrorism, and security intelligence solutions. Work across cloud, Kubernetes, hybrid, and on-premises environments.

Description

  • Create and maintain large-scale pipelines for data ingestion, transformation, and enrichment.
  • Develop and operate distributed data services with Java, Python, Kafka, and related technologies.
  • Architect data platforms that are scalable, resilient, and performant.
  • Build and refine data models for analytics, search, graph, and operational use cases.
  • Deploy and administer applications in Kubernetes environments.
  • Use AWS and/or GCP services while supporting hybrid and on-premises deployments.
  • Collaborate with customers, integration teams, and solution architects on successful implementations.
  • Monitor, diagnose, and improve platform performance, reliability, and scalability.
  • Support infrastructure automation, CI/CD, and broader platform engineering efforts.
  • Travel domestically and internationally when needed for customer engagements, workshops, and deployments.

Requirements

  • At least five years of experience in data engineering, software engineering, or platform engineering.
  • Strong programming skills in Java and/or Python.
  • Practical experience with Kubernetes and Docker-based containerized applications.
  • Experience using AWS, GCP, or another public cloud platform.
  • Background supporting or operating hybrid-cloud and on-premises environments.
  • Sound knowledge of distributed systems and multithreaded applications.
  • Experience with SQL and NoSQL databases.
  • Experience building and operating production-grade data pipelines.
  • Strong troubleshooting and operational capabilities.
  • Clear communication and effective collaboration skills.
  • Experience designing and operating multi-cluster Kubernetes environments.
  • Experience with data platforms running 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

  • Domestic and international travel may be required for customer engagements, workshops, and deployments.

Related Jobs