Lead Semantic Data Engineer
Core
Architect, build, and scale enterprise-grade knowledge graph solutions to integrate heterogeneous scientific datasets for advanced analytics and AI/ML-driven discovery in pharmaceutical research.
Role type
Lead Semantic Data Engineer
Builds
Scalable knowledge graph architectures and semantic data layers
Domain
Pharmaceutical R&D / Knowledge Graphs
Deliverable
production ML models
Required skills
Semantic web technology (RDF, SPARQL), Amazon Web Services (serverless), Data engineering (SQL, ETL), Python, DevSecOps (CI/CD, IaC, containers)
Preferred skills
Cheminformatics, AI/ML applications leveraging graph data
Technologies
Amazon Neptune, AWS Lambda, AWS Step Functions, CloudFormation, Terraform, Docker, Git, Jira, Confluence
Responsibilities
Design and implement scalable knowledge graph architectures; Build and manage graph data models representing biological entities; Drive adoption of graph technologies; Partner with platform teams to implement scalable infrastructure; Ensure performance, scalability, and governance of knowledge graph platforms; Collaborate with cross-functional teams to translate business needs into semantic models; Define and execute the knowledge graph roadmap; Mentor engineers and establish best practices in ontology development
Seniority
Lead, hands-on IC with mentorship responsibilities
