Semantic Data Engineer

MSD

. Design and implement scalable knowledge graph architectures integrating multimodal data such as omics, process, analytical, and lineage data .

Posted 11/2/2026full-timePrague • CzechiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable knowledge graph architectures, integrating multimodal data for advanced analytics in pharmaceutical research. Proficient in semantic web technologies and cloud infrastructure to support data-driven decision-making.

Highest-signal resume keywords

Semantic Web Technology StackAmazon Web Services (AWS)Graph Data ModelingPython ProgrammingDevSecOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

RDFSPARQLSQL QueriesETL JobsPythonCI/CDInfrastructure-as-CodeCloudFormationTerraformDocker

Soft Skills

CollaborationCommunication

Tools & Technologies

Amazon NeptuneServerless PipelinesAtlassian ToolsJiraConfluence

Industry Keywords

CheminformaticsPharmaceutical ResearchAI/ML ApplicationsGraph TechnologiesData Governance

Tech Stack

Tools & technologies

AWSDockerETLPythonSQLTerraform

About the role

Key responsibilities & impact

Design and implement scalable knowledge graph architectures integrating multimodal data such as omics, process, analytical, and lineage data
Build and manage graph data models for samples, processes, assays, targets, and biological relationships
Drive adoption of graph technologies including RDF, property graphs, SPARQL, and Cypher
Partner with platform teams to implement scalable infrastructure such as Amazon Neptune and 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
Build and scale enterprise-grade knowledge graph solutions supporting advanced analytics and decision-making in pharmaceutical research
Implement semantic data layers integrating heterogeneous scientific datasets for traceability, cross-domain insights, and AI/ML-driven discovery

Requirements

What you’ll need

Expertise in semantic web technology stack, including RDF and SPARQL
Experience with Amazon Web Services (AWS), particularly serverless services such as Lambda and Step Functions
Data engineering experience, including SQL queries and ETL jobs
Python programming experience
Experience with DevSecOps practices, including CI/CD, Git, infrastructure-as-code with CloudFormation or Terraform, and Docker
Cheminformatics and familiarity with pharmaceutical research
Exposure to AI/ML applications leveraging graph data
Experience with Atlassian tools such as Jira and Confluence
Ability to collaborate with enterprise teams
Visa sponsorship available
Valid driving license not required

Benefits

Comp & perks

Hybrid work arrangement
Visa sponsorship
No relocation required
10% travel requirements