Job Description

External Job Description

FADA is seeking a forward‑thinking DevOps Engineer to architect, automate, and optimize mission‑critical infrastructure supporting advanced GEOINT, imagery workflows, and ISR systems. This role ensures secure, scalable, cloud‑native environments and highly automated DevOps practices that enable rapid mission capability delivery.

Key Responsibilities

• Architect and deploy cloud‑native infrastructure (Azure/AWS) for GEOINT and imagery‑processing systems, including compute, storage, networking, IAM, and hybrid connectivity.
• Implement Infrastructure as Code (Terraform, Bicep, Ansible) to automate provisioning of geospatial pipelines, imagery clusters, and distributed compute.
• Develop Python automation for data ingestion, metadata workflows, monitoring, and deployment tasks.
• Build and optimize CI/CD pipelines (Azure DevOps, GitHub Actions, GitLab CI) for geospatial services and microservices.
• Deploy and manage Docker/Kubernetes (AKS/EKS) workloads, including GPU clusters, raster processing, and geospatial APIs.
• Implement observability solutions (Prometheus, Grafana, ELK, Azure Monitor, CloudWatch) for GEOINT workloads and platform reliability.
• Enhance resilience, scalability, and performance for EO/SAR ingestion, high‑volume raster data, and analytics services.
• Ensure compliance with cybersecurity controls, Zero Trust, encryption, and access governance.
• Design secure network architectures (VNet/VPC, firewalls, VPN/ExpressRoute, load balancing, service‑to‑service security).
• Troubleshoot cloud infrastructure, imagery pipelines, and deployment issues across environments.
• Maintain architecture documents, playbooks, governance standards, and runbooks.
• Collaborate with GEOINT engineers, data scientists, and software teams to meet mission and geospatial data requirements.

Qualifications

• Bachelor’s or Master’s in Computer Science, Cloud Engineering, GIS/Geospatial Technology, or related field.
• 7–10+ years in DevOps, Cloud, or Infrastructure Engineering.
• Strong Python skills for automation, APIs, and operational tooling.
• Experience with geospatial workflows, imagery systems, raster pipelines, STAC catalogs, or GIS platforms.
• Deep expertise in Azure/AWS networking, compute, IAM, security, and landing zone architectures.
• Proficiency with IaC (Terraform preferred), configuration automation, and Git workflows.
• Solid Kubernetes experience (architecture, orchestration, container management).
• Knowledge of PostGIS, geospatial formats (GeoTIFF, COG, WMTS, vector tiles), and metadata standards.
• Strong understanding of DNS, routing, VPNs, load balancers, firewalls, and service mesh.
• Experience with enterprise monitoring, logging, and incident response.
• Familiarity with cybersecurity, cloud governance, and compliance frameworks.

Preferred Skills

• DevOps automation for geospatial pipelines, EO/SAR engines, or raster indexing.
• Advanced Python for imagery processing, raster manipulation, metadata extraction, and parallel workflows.
• Knowledge of GIS tools (ArcGIS, QGIS), STAC/OGC standards, and EO imagery workflows (tiling, mosaicking, orthorectification).
• Familiarity with cloud EO platforms (SentinelHub, Google Earth Engine, OpenEO).
• Experience with GitOps (ArgoCD, Flux).
• Strong understanding of Kubernetes ingress/egress, service mesh, and securing geo‑microservices.
• Experience designing highly available architectures for mission‑critical geospatial workloads.
• Background in defense, ISR ecosystems, or secure operational enclaves.
• Ability to drive engineering standards, governance, documentation quality, and DevOps best practices.

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