What are the responsibilities and job description for the Scientific Computing Platform Engineer position at Jobs via Dice?
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Scientific Computing Platform Engineer
Location: LA / Remote
Primary Skills: Python, AWS S3, Linux, IAM/Okta integration, HPC and cluster computing environments, metadata management, workflow automation, and scientific computing.
Minimum experience: 5 Years.
Science Vault is currently a working but mostly manual data publishing workflow for research/scientific computing data. It publishes data from ASC/Cluster environments into an S3-backed, read-only storage model with metadata capture, access through Client website and controls tied to Okta, AD groups, and S3 permissions.
The immediate need is someone who can own the closing engineering work: stabilize the workflow, reduce manual steps, improve usability, and help make it supportable for broader Research use.
Core skills needed:
Strong Python scripting and CLI development
AWS S3 experience, including bucket structure, versioning, permissions, and access patterns
IAM/security awareness, ideally with Okta, AD groups, or enterprise auth integration
Linux/HPC environment familiarity, especially working from shared filesystems or cluster environments
Ability to work with metadata capture, validation, and structured data manifests
Practical debugging, logging, packaging, and operational hardening experience
Web app or lightweight portal development for self-service publishing/access
Familiarity with data cataloguing, FAIR metadata, MMDS, or scientific data management
Experience building supportable internal tools with documentation and handoff materials
Comfort working with scientists/research users to convert rough workflows into usable products
Scientific Computing Platform Engineer
Location: LA / Remote
Primary Skills: Python, AWS S3, Linux, IAM/Okta integration, HPC and cluster computing environments, metadata management, workflow automation, and scientific computing.
Minimum experience: 5 Years.
Science Vault is currently a working but mostly manual data publishing workflow for research/scientific computing data. It publishes data from ASC/Cluster environments into an S3-backed, read-only storage model with metadata capture, access through Client website and controls tied to Okta, AD groups, and S3 permissions.
The immediate need is someone who can own the closing engineering work: stabilize the workflow, reduce manual steps, improve usability, and help make it supportable for broader Research use.
Core skills needed:
Strong Python scripting and CLI development
AWS S3 experience, including bucket structure, versioning, permissions, and access patterns
IAM/security awareness, ideally with Okta, AD groups, or enterprise auth integration
Linux/HPC environment familiarity, especially working from shared filesystems or cluster environments
Ability to work with metadata capture, validation, and structured data manifests
Practical debugging, logging, packaging, and operational hardening experience
Web app or lightweight portal development for self-service publishing/access
Familiarity with data cataloguing, FAIR metadata, MMDS, or scientific data management
Experience building supportable internal tools with documentation and handoff materials
Comfort working with scientists/research users to convert rough workflows into usable products