At a Glance
- Tasks: Transform complex scientific data into structured models and enhance data value.
- Company: Leading tech firm focused on innovative data solutions.
- Benefits: Attractive salary, flexible hours, remote work options, and growth opportunities.
- Other info: Collaborative environment with a focus on professional development.
- Why this job: Join a team that bridges science and technology to make impactful data products.
- Qualifications: Experience in data engineering and familiarity with semantic technologies.
The predicted salary is between 60000 - 80000 £ per year.
The Engineers will focus on Scientific Data/Knowledge (specifically Metadata & Harmonization). This role is responsible for maximizing the value of our data assets over a lifetime to bring purpose to data by acting as translators of highly technical information from domain experts into an appropriate data model - complete with significant ontology and vocabulary - that can be utilized to effectively structure and index the data.
Specifically working with Product managers and R&D subject matter expertise to define the language (data models, ontology, standards, etc.) of science into data products by acting as the voice of Knowledgebase and interoperability/value of asset.
- Metadata harmonization/curation and large-scale dataset ingestion (structured, auditable transformations)
- Ontology alignment (eg, via OLS) and entity normalisation; schema-driven automation (eg, JSON)
- Knowledge graph/semantic technologies where applicable (RDF, SPARQL, Neo4j/GraphDB)
- API/ETL engineering and data pipeline delivery (eg, FastAPI, PostgreSQL) with cloud execution as required
Languages & Query: SPARQL, Scala, Python, and SQL.
Semantic Technologies: RDF/triple stores, OWL, SHACL, LinkML, and ontologies such as RAO.
Platforms & Infrastructure: Google Cloud Platform (GCP), BigQuery, Google Cloud Storage (GCS), and Infrastructure as Code (IaC).
Data Engineering: ETL processes, data harmonization, URI generation, and graph embedding machine learning pipelines.
Tools: GitHub/GitLab, Apache Jena, Protege, and Jira/Confluence, Top Quadrant (EDG), Apache Jena, Protégé, and Semaphore.
Aligned to EST hours.
Graph Engineers employer: Intuition IT Solutions Ltd
As a Graph Engineer at our innovative company, you will thrive in a collaborative work culture that values scientific exploration and data-driven decision-making. We offer competitive benefits, including professional development opportunities and a supportive environment that encourages growth and creativity, all while working in a dynamic location that fosters cutting-edge research and technology. Join us to make a meaningful impact on the future of data science and knowledge management.
Contact Details:
Intuition IT Solutions Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Graph Engineers
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of Graph Engineering on platforms like LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your knowledge.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Make sure you can confidently discuss metadata harmonization, ontology alignment, and the tools mentioned in the job description. Practice explaining complex concepts in simple terms!
✨Tip Number 3
Showcase your projects! If you've worked on any relevant data models or graph technologies, make sure to highlight them in your conversations. Having tangible examples can really set you apart from other candidates.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from our platform, and it gives you a better chance to stand out. Plus, it’s super easy to keep track of your application status!
We think you need these skills to ace Graph Engineers
Some tips for your application 🫡
Show Your Passion for Data:When writing your application, let us see your enthusiasm for data and how it can be transformed into valuable insights. Share any relevant experiences or projects that highlight your skills in metadata harmonization and data modelling.
Tailor Your Application:Make sure to customise your application to align with the job description. Use keywords from the role, like 'ontology', 'data models', and 'semantic technologies', to demonstrate that you understand what we’re looking for.
Be Clear and Concise:We appreciate clarity! Keep your application straightforward and to the point. Avoid jargon unless it’s necessary, and make sure your experience is easy to follow. We want to see your skills without wading through fluff.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Intuition IT Solutions Ltd
✨Know Your Data Models
Make sure you brush up on your understanding of data models, ontologies, and the specific technologies mentioned in the job description. Being able to discuss how you would approach metadata harmonization or schema-driven automation will show that you're not just familiar with the concepts but can also apply them practically.
✨Speak Their Language
When discussing your experience, use terminology that aligns with the role. If they mention SPARQL, RDF, or Neo4j, weave these terms into your answers. This demonstrates that you understand the technical landscape and can communicate effectively with both technical and non-technical stakeholders.
✨Showcase Your Problem-Solving Skills
Prepare examples of past projects where you tackled complex data challenges. Highlight your thought process and the steps you took to achieve successful outcomes. This will illustrate your ability to act as a translator between domain experts and data models, which is crucial for this role.
✨Familiarise Yourself with Their Tools
Get to know the tools and platforms mentioned in the job description, like Google Cloud Platform, FastAPI, and GitHub. If you have experience with these, be ready to discuss it. If not, do a bit of research so you can speak confidently about how you would approach using them in your work.
