Systems Engineer

Johns Hopkins Applied Physics Laboratory
Laurel, MD, United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$135,000.0 - $175,000.0
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Data Analysis Systems Engineering Microsoft Azure Bash Shell Cloud Computing Data Infrastructure Extract Transform Load (ETL) Monitoring of Systems Python (Programming Language) Network Security Linux System Administration
+8 more
Ansible Software Requirements Analysis SQL Databases Scripting Infrastructure Automation Frameworks Deployment Automation Terraform Data Pipelines

Job description

Johns Hopkins Applied Physics Laboratory (APL) seeks a Systems Engineer for Data & Analysis Infrastructure to design, build, and sustain secure, scalable data platforms that power mission-critical research in national security, space, and health. You will architect and integrate data pipelines, storage, and analytics environments; collaborate with multidisciplinary teams to translate mission needs into resilient systems; and apply automation, monitoring, and optimization to ensure high performance and reliability. Join APL’s mission-driven, collaborative culture with strong support for innovation and professional growth., * Design, implement, and maintain secure, scalable data and analytics infrastructure to support research and mission programs.

  • Integrate data sources, pipelines, and storage solutions to enable advanced modeling, simulation, and analytics.
  • Collaborate with researchers, engineers, and analysts to translate mission needs into technical system requirements.
  • Monitor, optimize, and troubleshoot system performance, reliability, and security in production environments.
  • Automate deployment, configuration, and monitoring using modern Dev
  • Ops and infrastructure-as-code tools.
  • Document architectures, interfaces, and operational procedures in accordance with APL and sponsor standards.

Requirements

  • Systems engineering
  • Data platform architecture
  • ETL and data pipelines
  • SQL and No
  • SQL databases
  • Cloud platforms (AWS/Azure/GCP)
  • Linux administration
  • Networking and security fundamentals
  • Infrastructure as Code (e.g., Terraform, Ansible)
  • Monitoring and observability tools
  • Scripting (Python, Bash or similar)

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