Platform Software Engineer - 19312

Northrop Grumman•Roy, UT

21d•$98,400 - $184,200•Onsite

About The Position

Northrop Grumman Defense Systems is seeking a Principal/Senior Principal Platform Software Engineer to join our team. This is a dual-level position supporting the Sentinel program, located in Roy, Utah. This requisition is open at the T03 and T04 levels, with the final level determined by the selected candidate's qualifications and experience. The role involves contributing to the design, deployment, and day-to-day operation of the Sentinel data platform, which is built on modern cloud services to enable secure, reliable, and scalable data enablement for the program. Northrop Grumman offers incredible opportunities to work on revolutionary systems, fostering a culture of intellectual curiosity and a drive to achieve the impossible. We provide competitive pay and comprehensive benefits, aiming to help employees grow and achieve their goals.

Requirements

T03: 5 Years with Bachelors in Science; 3 Years with Masters; 1 Year with PhD, 4 additional years of experience may be used in lieu of a degree.
T04: 8 Years with Bachelors in Science; 6 Years with Masters; 4 Years with PhD, 4 additional years of experience may be used in lieu of a degree.
Must have an active U.S. Government DoD Secret security clearance at time of application, current and within scope.
Experience deploying and supporting cloud-native infrastructure using Infrastructure as Code (IaC) principles.
Working knowledge of Terraform or similar infrastructure automation frameworks.
Experience with modern cloud platforms such as AWS or Azure.
Understanding of container technologies including Docker and Kubernetes.
Experience developing and maintaining CI/CD pipelines using tools such as GitLab CI, GitHub Actions, Azure DevOps, Jenkins, or similar technologies.
Experience using source control systems such as Git within collaborative software development environments.
Ability to develop automated validation, integration, or system tests that improve platform reliability and deployment confidence.
Familiarity with scripting or programming languages such as Python, Bash, Go, or PowerShell for platform automation.
Understanding of Linux operating systems, networking fundamentals, and infrastructure troubleshooting.
Ability to diagnose technical issues across infrastructure, networking, and application layers.
Strong written and verbal communication skills with the ability to interact directly with customers, stakeholders, and cross-functional engineering teams.

Nice To Haves

Experience deploying or administering Databricks workspaces or similar enterprise data platforms.
Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related STEM discipline.
Experience implementing Terraform modules and managing infrastructure through GitOps workflows.
Experience with Kubernetes platform administration and Helm.
Familiarity with cloud identity and access management, secrets management, and security best practices.
Experience supporting data platforms utilizing technologies such as Spark, Kafka, Airflow, object storage, or lakehouse architectures (Delta Lake, Apachie Iceberg).
Experience developing automated platform health checks, regression testing, and infrastructure validation frameworks.
Familiarity with observability technologies including Prometheus, Grafana, OpenTelemetry, or equivalent monitoring platforms.
Experience working within Agile or DevSecOps development environments.
Demonstrated ability to collaborate directly with customers to gather requirements, resolve technical issues, and improve platform capabilities.
Self-starter with a strong sense of ownership, curiosity, and commitment to delivering high-quality engineering solutions.

Responsibilities

Implement and maintain cloud-native infrastructure and shared platform services using Infrastructure as Code (Terraform or similar) for Databricks workspaces, networking, storage, and security controls.
Build and support CI/CD pipelines that automate provisioning, configuration, and validation of platform components, including automated testing and quality gates.
Collaborate with data engineering and data science teams to onboard new workloads, standardize patterns for ingestion/curation/serving, and resolve platform-related issues.
Configure and support containerized services (Docker, Kubernetes) and integration with the broader platform ecosystem (e.g., Airflow or other orchestration, object storage, observability stack).
Implement monitoring, logging, alerting, and automated health checks to ensure platform reliability, availability, and performance.
Troubleshoot issues across infrastructure, networking, and application layers, driving root-cause analysis and permanent corrective actions.
Participate in Agile/DevSecOps development continuously improving tooling, processes, and documentation for the platform.
Operate within security and compliance constraints, following cloud and data security best practices and collaborating with security and governance teams.