IT Semantic Engineer - RDT Data Platforms
⚲ Poznań, Nowe Miasto, Warszawa, Mokotów
14 175–26 325 zł brutto / mies.
Wymagania
- Python
- Neo4j
- R
- Docker
- Kubernetes
- ArgoCD
- Helm
- OpenAI API
- Linux
- Grafana
- Terraform
- OpenStack
- OpenShift
Opis stanowiska
Nasze wymagania:
Education / Experience
Demonstrated experience handling enterprise-scale data engineering projects and managing complex semantic web systems and knowledge graphs.
Experience configuring, deploying, and maintaining infrastructure components in a Kubernetes environment using GitOps automation.
Experience working with validated or qualified platforms (GxP) is a plus.
Technical Skills
Experience: Senior-level experience in data engineering, software engineering, or semantic web engineering with strong Python coding skills, a proven track record of autonomous delivery, and a focus on knowledge graphs or AI system enablement.
Semantic & Graph Technologies: Hands-on experience with Graph databases (Ontotext GraphDB preferred, Neo4j) and core semantic web standards (RDF, OWL, SPARQL and ontology design).
APIs & AI Protocols: Deep understanding of GraphQL API design and hands-on experience with the Model Context Protocol (MCP) to expose data tools to LLMs.
DevOps & Infrastructure: Experience configuring, deploying, and managing containerized workloads within enterprise Kubernetes (Rancher/RKE2) environments.
GitOps & CI/CD: Expert proficiency in Git-based workflows using trunk-based development, automated deployments via ArgoCD, and application packaging with Helm charts.
Security & Networking: Solid practical understanding of secrets management using HashiCorp Vault (and Vault Secrets Operator), Linux networking, TLS configurations, and navigating corporate proxy/gateway patterns.
Data Strategy: Practical familiarity with FAIR principles and their implementation across enterprise data architectures.
Workflow Orchestration: Practical experience with distributed workflow management platforms (e.g. Temporal) is a plus.
Search & Indexing: Hands-on experience deploying, configuring, and managing OpenSearch for enterprise data retrieval and search capabilities is a plus.
Additional Qualifications
Exceptional communication and collaboration skills, with the proven ability to engage effectively with both technical audiences (like data scientists) and non-technical business stakeholders.
O projekcie:
The IT Semantic Engineer is responsible for leading, designing, developing, and maintaining our enterprise-level semantic hub. This platform serves as the foundational data layer bridging the gap between vast enterprise knowledge and advanced AI systems.
In this role, you will integrate diverse data and metadata sources into a unified knowledge graph, design common ontologies to expose disparate datasets uniformly, build robust APIs and integration protocols for AI consumption. The ultimate goal is to provide high-precision enterprise context to AI assistants and intelligent agents—grounding their responses, enabling reliable workflow execution, and eliminating AI hallucinations.
Zakres obowiązków:
Scope / Content Leadership: Leads the design, build, and maintenance of scalable data pipelines and graph architectures. Independently drives data integration projects from ingestion to semantic transformation, establishing unified enterprise ontologies.
Accountability / Problem Solving: Solves complex data modeling, ingestion, and querying challenges. Evaluates, benchmarks, and optimizes the performance of data access tools to ensure AI systems fetch enterprise context efficiently, accurately, and with minimal latency.
Stakeholder Management: Collaborates directly with data owners, domain experts, and AI application teams to thoroughly understand business requirements. Translates complex business use cases into robust schemas and standardized data endpoints.
Impact / Strategy: Drives the technical evolution of the hub’s delivery architecture. Implements robust strategies for distributed data indexing, orchestration, and access, while embedding FAIR principles (Findable, Accessible, Interoperable, Reusable) across all workflows.
Complexity / Product Size: Manages a highly interconnected, large-scale enterprise knowledge system. Integrates complex, multi-source metadata systems into a uniform layer, navigating advanced infrastructure and enterprise gateway patterns to maintain seamless, automated deployments.
Oferujemy:
Salary range 14 175-26 325 PLN gross based on the employment contract.
Annual bonus payment based on your performance.
Dedicated training budget (training, certifications, conferences, diversified career paths etc.).
Recharge Fridays (2 Fridays off per quarter available).
Take time Program (up to 3 months of leave to use for any purpose).
Vacation subsidy available.
Flex Location (possibility to perform our work from different places in the world for a certain period of time).
Take Time for Charity (additional paid leave of maximum 2 weeks to engage in the charity action of your choice).
Private healthcare (LuxMed packages), group life insurance (UNUM) and Multisport.
Stock share purchase additions.
Yearly sales of company laptops and cars and many more!
Education / Experience
Demonstrated experience handling enterprise-scale data engineering projects and managing complex semantic web systems and knowledge graphs.
Experience configuring, deploying, and maintaining infrastructure components in a Kubernetes environment using GitOps automation.
Experience working with validated or qualified platforms (GxP) is a plus.
Technical Skills
Experience: Senior-level experience in data engineering, software engineering, or semantic web engineering with strong Python coding skills, a proven track record of autonomous delivery, and a focus on knowledge graphs or AI system enablement.
Semantic & Graph Technologies: Hands-on experience with Graph databases (Ontotext GraphDB preferred, Neo4j) and core semantic web standards (RDF, OWL, SPARQL and ontology design).
APIs & AI Protocols: Deep understanding of GraphQL API design and hands-on experience with the Model Context Protocol (MCP) to expose data tools to LLMs.
DevOps & Infrastructure: Experience configuring, deploying, and managing containerized workloads within enterprise Kubernetes (Rancher/RKE2) environments.
GitOps & CI/CD: Expert proficiency in Git-based workflows using trunk-based development, automated deployments via ArgoCD, and application packaging with Helm charts.
Security & Networking: Solid practical understanding of secrets management using HashiCorp Vault (and Vault Secrets Operator), Linux networking, TLS configurations, and navigating corporate proxy/gateway patterns.
Data Strategy: Practical familiarity with FAIR principles and their implementation across enterprise data architectures.
Workflow Orchestration: Practical experience with distributed workflow management platforms (e.g. Temporal) is a plus.
Search & Indexing: Hands-on experience deploying, configuring, and managing OpenSearch for enterprise data retrieval and search capabilities is a plus.
Additional Qualifications
Exceptional communication and collaboration skills, with the proven ability to engage effectively with both technical audiences (like data scientists) and non-technical business stakeholders.
O projekcie:
The IT Semantic Engineer is responsible for leading, designing, developing, and maintaining our enterprise-level semantic hub. This platform serves as the foundational data layer bridging the gap between vast enterprise knowledge and advanced AI systems.
In this role, you will integrate diverse data and metadata sources into a unified knowledge graph, design common ontologies to expose disparate datasets uniformly, build robust APIs and integration protocols for AI consumption. The ultimate goal is to provide high-precision enterprise context to AI assistants and intelligent agents—grounding their responses, enabling reliable workflow execution, and eliminating AI hallucinations.
Zakres obowiązków:
Scope / Content Leadership: Leads the design, build, and maintenance of scalable data pipelines and graph architectures. Independently drives data integration projects from ingestion to semantic transformation, establishing unified enterprise ontologies.
Accountability / Problem Solving: Solves complex data modeling, ingestion, and querying challenges. Evaluates, benchmarks, and optimizes the performance of data access tools to ensure AI systems fetch enterprise context efficiently, accurately, and with minimal latency.
Stakeholder Management: Collaborates directly with data owners, domain experts, and AI application teams to thoroughly understand business requirements. Translates complex business use cases into robust schemas and standardized data endpoints.
Impact / Strategy: Drives the technical evolution of the hub’s delivery architecture. Implements robust strategies for distributed data indexing, orchestration, and access, while embedding FAIR principles (Findable, Accessible, Interoperable, Reusable) across all workflows.
Complexity / Product Size: Manages a highly interconnected, large-scale enterprise knowledge system. Integrates complex, multi-source metadata systems into a uniform layer, navigating advanced infrastructure and enterprise gateway patterns to maintain seamless, automated deployments.
Oferujemy:
Salary range 14 175-26 325 PLN gross based on the employment contract.
Annual bonus payment based on your performance.
Dedicated training budget (training, certifications, conferences, diversified career paths etc.).
Recharge Fridays (2 Fridays off per quarter available).
Take time Program (up to 3 months of leave to use for any purpose).
Vacation subsidy available.
Flex Location (possibility to perform our work from different places in the world for a certain period of time).
Take Time for Charity (additional paid leave of maximum 2 weeks to engage in the charity action of your choice).
Private healthcare (LuxMed packages), group life insurance (UNUM) and Multisport.
Stock share purchase additions.
Yearly sales of company laptops and cars and many more!
🔍 Dekoder Ogłoszenia
🔴
proven track record of autonomous delivery
Oczekiwana samodzielna praca bez dużego wsparcia zespołu lub mentora