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Tech Stack
Tools & technologiesAirflowDockerJenkinsKafkaKubernetesLinuxPython
About the role
Key responsibilities & impact- Build and maintain demos and prototypes in collaboration with internal teams and external partners
- Develop intimate knowledge of the Graphwise Platform components and capabilities
- Responsible for graph building and consumption tasks, including, but not limited to manual modelling and design and development of automated graph manipulation pipelines
- Do some code development when required for the tasks centered around the Graph processing
- Interact and communicate effectively with internal and external stakeholders to ensure the successful execution of the responsibilities
Requirements
What you’ll need- At least 3 years of industry experience with responsibilities in at least one of the following areas: data engineering, knowledge engineering, technical consulting
- Know-how and experience with data modelling and data engineering for heterogeneous sources, including APIs, document repositories, structured data, and unstructured content
- Experience designing and maintaining data processing and orchestration pipelines, with technologies such as Databricks, Snowflake, Airflow, Talend, Kafka… or related
- Experience with n8n is a plus
- Proficiency in Python scripting language, and experience with REST APIs and version control systems
- Experience with devops related tasks, including technologies such as Docker, Linux, Jenkins and K8S, is highly desirable
- Technical background around software development, databases, software and system architecture
- Experience using NLP, machine learning or similar to analyse, classify, and extract data from documents
- Experience in solution development with the Semantic Web technology stack (RDF, SPARQL, OWL, linked data etc.) would be highly desirable
- In particular, experience working with RDF-based graph databases, especially GraphDB, will be considered a plus
- Knowledge and experience in requirements engineering, ability to translate business problems into technical requirements
- Experience with modern AI technologies, in particular LLMs, RAG techniques and Agentic AI
- Proactivity and strong initiative, ability to work independently and unsupervised
- An inquiring mind, intense curiosity, interdisciplinary awareness as well as a strong desire to innovate in/contribute to the areas of Agentic AI and Knowledge Graph Systems
- Strong communication skills and the ability to communicate with stakeholders at various technical levels, including non-technical people
- Excellent skills in both written and spoken English
- Ability to effectively and simultaneously manage work from multiple projects
- Good time management skills and ability to prioritise tasks
Benefits
Comp & perks- A Career development path, through training, hands-on experience, time for innovation, and many more
- A friendly and professional international team and working environment in a rapidly expanding tech and AI company
- Exposure to the newest technologies in AI and knowledge graphs space
- A workplace in an organization that is committed to sustainability and responsible business practices
- Flexible working hours and benefits that reflect our belief that a healthy work-life balance is a key driver of efficiency
- Invitation to company-sponsored social activities and additional team building activities throughout the year
- A good work-life balance with the possibility to work from home up to 3 days per week and flexible working hours
- And of course we offer free tea, coffee, fruit and snacks
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringknowledge engineeringdata modellingdata processing pipelinesorchestration pipelinesPythonREST APIsNLPmachine learningSemantic Web
Soft Skills
strong communication skillsproactivityinitiativeability to work independentlycuriosityinterdisciplinary awarenessdesire to innovateability to manage multiple projectstime managementprioritisation