Lead Semantic Data Engineer — MSD

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Lead Semantic Data Engineer

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Mám zájem Přizpůsobit životopis

Získej víc odpovědí od zaměstnavatelů

Pošli zaměstnavateli životopis na míru během pár minut.

Přizpůsobit životopis

Koho hledáme

Semantic web technology stack (e.g., RDF data format, SPARQL query language)
Amazon Web Services, 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)

Co budeš dělat

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
Define and execute the knowledge graph roadmap aligned with enterprise data product strategy
Mentor engineers and establish best practices in ontology development, modeling, and graph engineering
Drive adoption of knowledge graph capabilities across use cases and programs

O pozici

Our company is seeking a lead semantic data engineer to architect, build, and scale enterprise-grade knowledge graph solutions that power advanced analytics and decision-making in pharmaceutical research. This role will lead 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.

Benefity

Exciting work in a great team, global projects, international environment
Opportunity to learn and grow professionally within the company globally
Pension and health (Canadian Medical) contributions
Internal reward system plus referral program
5 weeks annual leave, 5 sick days, 15 days of certified sick leave paid above statutory requirements annually, 40 paid hours annually for volunteering activities, 12 weeks of parental contribution
Cafeteria for tax free benefits according to your choice (meal vouchers, sport, culture, health, travel, etc.), Multisport card, Vodafone, Raiffeisen Bank and Foodora discount programs
Up-to-date laptop and iPhone, parking in the garage, showers, refreshments
Competitive salary, incentive pay, and many more