Semantic Engineer - RDT Data Platforms

14.1k - 26.3k PLN14 100 - 26 300 PLN/ mies./ mies.UoPUmowa o pracę (brutto)

SeniorOn-site·WarszawaFull-time·Umowa o pracę

#479014·Dodano wczoraj·0

Źródło: Roche

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Tech Stack / Keywords

PythonGraphDBNeo4jRDFOWLSPARQLGraphQLModel Context ProtocolKubernetes ArgoCD

Podsumowanie oferty

Lead the development of an enterprise semantic hub that connects enterprise data and knowledge with AI systems. Build knowledge graphs, unified ontologies, data integrations and APIs to provide context for AI assistants and agents.

Wymagania

Experience handling enterprise-scale data engineering projects and managing semantic web systems and knowledge graphs.
Experience configuring, deploying, and maintaining infrastructure in a Kubernetes environment using GitOps automation.
Senior-level experience in data engineering, software engineering, or semantic web engineering, with strong Python coding skills and a focus on knowledge graphs or AI system enablement.
Hands-on experience with graph databases, such as Neo4j, and semantic web standards including RDF, OWL, SPARQL, and ontology design.
Deep understanding of GraphQL API design and hands-on experience with the Model Context Protocol (MCP) to expose data tools to LLMs.
Experience managing containerized workloads in enterprise Kubernetes environments, including Rancher/RKE2.
Expert proficiency in Git-based workflows, trunk-based development, automated deployments using ArgoCD, and application packaging with Helm charts.
Practical understanding of secrets management using HashiCorp Vault and Vault Secrets Operator, Linux networking, TLS configurations, and corporate proxy and gateway patterns.
Familiarity with FAIR principles and their implementation across enterprise data architectures.
Strong communication and collaboration skills, including engaging with technical and non-technical stakeholders.

Nice to have:

Experience working with validated or qualified platforms (GxP).
Experience with Ontotext GraphDB.
Practical experience with distributed workflow management platforms such as Temporal.
Experience deploying, configuring, and managing OpenSearch for enterprise data retrieval and search.

Obowiązki

Scope / Content Leadership:

Lead the design, build, and maintenance of scalable data pipelines and graph architectures.
Drive data integration projects from ingestion to semantic transformation and establish unified enterprise ontologies.

Accountability / Problem Solving:

Solve complex data modeling, ingestion, and querying challenges.
Evaluate, benchmark, and optimize data access tools so AI systems can retrieve enterprise context efficiently, accurately, and with minimal latency.

Stakeholder Management:

Collaborate with data owners, domain experts, and AI application teams to understand business requirements.
Translate business use cases into schemas and standardized data endpoints.

Impact / Strategy:

Drive the technical evolution of the hub’s delivery architecture.
Implement strategies for distributed data indexing, orchestration, and access, embedding FAIR principles across workflows.

Complexity / Product Size:

Manage a large-scale enterprise knowledge system.
Integrate multi-source metadata systems into a uniform layer and navigate infrastructure and enterprise gateway patterns to maintain automated deployments.

Benefity

Annual performance-based bonus with a 15% target.
Private healthcare packages through LuxMed.
Group life insurance through UNUM.
Multisport.
Recharge Fridays: two Fridays off per quarter.
Take Time Program: up to three months of leave for any purpose.
Up to two weeks of additional paid leave to participate in a charity activity of your choice.
Stock share purchase additions.
Yearly sales of company equipment.

Premie

Opieka zdrowotna

Ubezpieczenie

Karta sportowa

Płatny urlop

Udziały pracownicze

Roche

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