Specialist, Semantic Data Engineer
Quick Summary
Required Skills:Amazon Web Services (AWS), CI/CD, Collaboration, Communication, DevSecOps, Extract Transform Load (ETL), Graph Databases, Infrastructure As Code (IaC), Python (Programming Language),
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.
Responsibilities
~1 min read- →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
- 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)
- 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
What We Offer
~1 min readNice to Have
~1 min readRequirements
~1 min readLocation & Eligibility
About this job
- Posted
- Today
Listing Details
- Posted
- November 2, 2026
- First seen
- November 2, 2026
- Last seen
- November 2, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 49%
- Scored at
- November 2, 2026
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