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Build and maintain production knowledge graphs in Stardog using semantic web standards, ontology modeling, SPARQL, virtual mappings, Python, and SQL. Integrate life science data sources, implement data quality and validation, automate CI/CD deployments, support governance and lineage, and collaborate with subject matter experts to develop defensible semantic models.

Build and deploy production knowledge graphs in Stardog using semantic web standards, ontology modeling, SPARQL, mappings, and virtual graphs. Integrate life science data from diverse sources, automate graph builds and CI/CD workflows with Python, enforce quality and validation, and support governance, lineage, and reusable semantic assets. Collaborate with subject matter experts and data and AI engineering teams in agile environments.

Administer, design, and evolve high-performance computing platforms across on-premises and cloud environments. Support scientific applications, workflows, infrastructure, migrations, and modernization initiatives. Responsibilities include Linux administration, cloud infrastructure deployment, CloudOps, infrastructure as code, performance tuning, monitoring, troubleshooting, documentation, architecture, compliance, and customer consulting. The role also mentors junior engineers and serves as an escalation point across multiple client engagements.

Support AWS application migrations and modernization for scientific computing platforms. Build and manage cloud infrastructure using CloudOps, IaC, containers, and AWS services including EC2, RDS, S3, ECS/EKS, Glue, EMR, and Athena. Troubleshoot operational issues, restore services, ensure security and regulatory compliance, and transition modernized services to operations teams. The role also contributes to cloud architecture, roadmaps, documentation, and infrastructure best practices for Life Sciences customers.