Specialist, Semantic Data Engineer

Job Description

Our company is seeking a semantic data engineer to build, and scale enterprise-grade knowledge graph solutions that power advanced analytics and decision-making in pharmaceutical research. This role will implement the design of semantic data layers that integrate heterogeneous scientific datasets, enabling end-to-end traceability, cross-domain insights, and AI/ML-driven discovery. The ideal candidate will combine deep expertise in knowledge graphs, ontology engineering, and data engineering, with strong domain awareness in pharmaceutical R&D.

Key responsibilities

• Design and implement scalable knowledge graph architectures to integrate multi-modal data (e.g., omics, process, analytical, lineage)
• Build and manage graph data models representing entities such as samples, processes, assays, targets, and biological relationships
• Drive adoption of graph technologies (e.g., RDF, property graphs, SPARQL/Cypher)
• Partner with platform teams to implement scalable infrastructure (e.g., Amazon Neptune, serverless pipelines)
• Ensure performance, scalability, and governance of knowledge graph platforms
• Collaborate with product managers, scientists, data engineers, and AI/ML teams to translate business needs into semantic models

Required experience and skills

• Semantic web technology stack (e.g., RDF data format, SPARQL query language)
• Amazon Web Services (AWS), particularly the serverless services (e.g., Lambda, Step Functions)
• Data engineering (e.g., SQL queries, ETL jobs)
• Programming in Python
• Experience with DevSecOps practices like continuous integration (CI) and continuous delivery (CD), source code version control (e.g., Git), infrastructure-as-code (e.g., CloudFormation, Terraform), and containers (e.g., Docker)

Desired experience and skills

• Cheminformatics and familiarity with the pharmaceutical research
• Exposure to AI/ML applications leveraging graph data
• Good communication and collaboration skills, and ability to collaborate with other teams to develop solutions
• Experience with Atlassian stack of tools for agile software development (e.g., Jira, Confluence)
• Demonstrate growth mindset and ability to work with enterprise teams

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