Data Engineer

Cognyte

14d•Remote

About The Position

At Cognyte, you’ll collaborate with expert colleagues around the globe to solve problems most people will never even know exist! You’ll be part of building unique solutions shaped by real investigative methodologies, enabling our customers to identify, investigate, visualize and prevent criminal, terror and security threats worldwide. These solutions are used by law enforcement, national security, and national and military intelligence agencies in almost 100 countries to turn massive, diverse data into clear, actionable intelligence for a safer world. We are looking for a talented and hands-on Data Engineer to join our Delivery team. This role is ideal for engineers who are passionate about building scalable data platforms and distributed systems while working across modern cloud and infrastructure technologies. You will design, develop, and operate large-scale data pipelines and services that process massive volumes of structured and unstructured data in both cloud (AWS/GCP/Azure) and on-premises environments. The ideal candidate combines strong software engineering skills with infrastructure expertise, including Kubernetes, containerization, cloud-native architectures, and platform operations.

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.

Nice To Haves

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.

Responsibilities

Design, develop, and maintain large-scale data ingestion, transformation, and enrichment pipelines.
Build and operate distributed data processing services using technologies such as 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.
Ability to travel domestically and internationally as needed for customer engagements, workshops, and deployments.